A B C D E F G H I L M N O P R S T U V W X

A

AbstractPopulation - Class in geneticWedge.gp
AbstractPopulation is the parent of all Population objects.
AbstractPopulation() - Constructor for class geneticWedge.gp.AbstractPopulation
 
AbstractPopulation.FitnessFunction - Enum in geneticWedge.gp
The FitnessFunction is used to select Individuals from a Population for breeding.
AbstractPopulation.SelectionMethod - Enum in geneticWedge.gp
SelectionMethod determines how Individuals are selected for breeding.
addGPDoneHandler(GPEventHandler) - Method in class geneticWedge.gp.PopulationV
 
addGPGenerationHandler(GPEventHandler) - Method in class geneticWedge.gp.PopulationV
 
AdditionFunction - Class in geneticWedge.gp.function
AdditionFunction is a Function that takes 2 inputs and outputs their sum as an output.
AdditionFunction() - Constructor for class geneticWedge.gp.function.AdditionFunction
Constructor
addMutatedConstant(double) - Method in class geneticWedge.gp.PopulationDescriptor
When CONSTANT_VALUE mutation is included as a mutation operation, new Constant objects may be created.
allFitnesses - Variable in class geneticWedge.gp.AbstractPopulation
An array containing the (training) fitnesses of all Individuals in this Population
ANDFunction - Class in geneticWedge.gp.function
ANDFunction is a Function that takes 2 inputs and outputs +1 if both numbers are positive, -1 otherwise.
ANDFunction() - Constructor for class geneticWedge.gp.function.ANDFunction
Constructor
aurocSampleSize - Variable in class geneticWedge.gp.AbstractPopulation
The number of points used to estimate the AUROC (and AOREC).
averageTrainFitness - Variable in class geneticWedge.gp.AbstractPopulation
The average (mean) training fitness of all members of the population
averageValidationFitness - Variable in class geneticWedge.gp.AbstractPopulation
The average (mean) validation fitness of all members of the population

B

bestIndex - Variable in class geneticWedge.gp.AbstractPopulation
The index of the Individual with the best (training) fitnesses
bestTrainFitness - Variable in class geneticWedge.gp.AbstractPopulation
The best training fitness obtained by any member of the current population
bestTrainFitnessSoFar - Variable in class geneticWedge.gp.AbstractPopulation
The best validation fitness obtained by any member of the current population in any generation so far
bestValidationFitness - Variable in class geneticWedge.gp.AbstractPopulation
The best validation fitness obtained by any member of the current population
bestValidationFitnessSoFar - Variable in class geneticWedge.gp.AbstractPopulation
The best training fitness obtained by any member of the current population in any generation so far
BipolarSigmoidFunction - Class in geneticWedge.gp.function
BipolarSigmoidFunction is a unary function commonly used in Artificial Neural Networks.
BipolarSigmoidFunction() - Constructor for class geneticWedge.gp.function.BipolarSigmoidFunction
Constructor

C

characters(char[], int, int) - Method in class geneticWedge.gp.io.XMLTreeHandler
Receive notification of character data inside an element.
clone() - Method in class geneticWedge.gp.Individual
Creates a clone of this Individual, containing the same components in the same tree structure
collectTransmissionInfo(boolean) - Method in class geneticWedge.gp.Crossover
If set to true, collectTransmissionInfo saves information concerning the relationship between parent and offspring during crossover operations
collectTransmissionInfo(boolean) - Method in class geneticWedge.gp.Mutation
If set to true, collectTransmissionInfo saves information concerning the relationship between parent and offspring during mutation operations as well as the mutation operation that occurred.
collectTransmissionInfo(boolean) - Method in class geneticWedge.gp.Population
If set to true, information concerning the relationship between parents and offspring will be saved.
Component - Class in geneticWedge.gp
Component is the parent class of all nodes (Functions and Terminals) within a GP tree.
Component() - Constructor for class geneticWedge.gp.Component
 
Constant - Class in geneticWedge.gp
Constant is a type of terminal within a GP subtree.
Constant(double) - Constructor for class geneticWedge.gp.Constant
The constructor sets the value of a Constant.
CosineFunction - Class in geneticWedge.gp.function
CosineFunction is a Function that takes 1 input and outputs its cosine as an output.
CosineFunction() - Constructor for class geneticWedge.gp.function.CosineFunction
constructor
cross(Individual, Individual, boolean, Input[], Constant[], int, int) - Method in class geneticWedge.gp.Crossover
This method returns an array of Individuals created by crossing 2 parents (ind1 and ind2).
Crossover - Class in geneticWedge.gp
Crossover performs crossover ('sexual' recombination) between 2 Individuals, generating 1 or 2 offspring.
Crossover() - Constructor for class geneticWedge.gp.Crossover
The default constructor creates a Crossover with default parameters.
Crossover(double, int) - Constructor for class geneticWedge.gp.Crossover
Create a Crossover object.
CSVReader - Class in geneticWedge.gp.io
This class contains static methods for reading csv (comma-separated value) files and returning StringData or NumericData objects.
CSVReader() - Constructor for class geneticWedge.gp.io.CSVReader
 
CSVWriter - Class in geneticWedge.gp.io
This class contains static methods for writing data to csv files
CSVWriter() - Constructor for class geneticWedge.gp.io.CSVWriter
 

D

DataAcquirer - Class in geneticWedge.gp.dataAnalysis
DataAcquirer allows the performance of various statistical operations on a dataset.
DataAcquirer(Population) - Constructor for class geneticWedge.gp.dataAnalysis.DataAcquirer
Constructor takes a Population object as an argument, allowing the extraction of information from a particular Population.
DataAcquirer.ScalarData - Enum in geneticWedge.gp.dataAnalysis
ScalarData refer to scalar properties of an Individual.
DataAcquirer.VectorData - Enum in geneticWedge.gp.dataAnalysis
VectorData refer to the balance of components within each individual.
DemicPopulation - Class in geneticWedge.gp
DemicPopulation is an extension of Population that allows only local breeding, and tournaments are perfomed within a local 'deme'.
DemicPopulation(int, int, int, PopulationDescriptor) - Constructor for class geneticWedge.gp.DemicPopulation
DemicPopulations have restricted breeding between nearby Individuals.
DemoUtils - Class in geneticWedge.gp.demo
 
DemoUtils() - Constructor for class geneticWedge.gp.demo.DemoUtils
 
denormaliseData(double[][]) - Method in class geneticWedge.gp.io.NumericData
This method uses the normalisation constants set as a side effect in normaliseData().
denormaliseData(double[], int) - Method in class geneticWedge.gp.io.NumericData
This method uses the normalisation constants set as a side effect in normaliseData().
DisplayTree - Class in geneticWedge.gp.display
DisplayTree is a demo program that displays randomly generated GP trees in a TreeFrame.
DisplayTree() - Constructor for class geneticWedge.gp.display.DisplayTree
 
DivisionFunction - Class in geneticWedge.gp.function
DivisionFunction is a Function that takes 2 inputs and outputs the first divided by the second.
DivisionFunction() - Constructor for class geneticWedge.gp.function.DivisionFunction
constructor

E

endElement(String, String, String) - Method in class geneticWedge.gp.io.XMLTreeHandler
Receive notification of the end of an element.
endPrefixMapping(String) - Method in class geneticWedge.gp.io.XMLTreeHandler
Receive notification of the end of a Namespace mapping.
equals(Constant) - Method in class geneticWedge.gp.Constant
Returns true if this Constant has the same numerical value as the comparison object.
equals(Individual) - Method in class geneticWedge.gp.Individual
This method will only return true if all of the nodes in the comparison Individual refer to the same Component objects as the reference Individual.
error(SAXParseException) - Method in class geneticWedge.gp.io.XMLTreeHandler
Receive notification of a recoverable parser error.
EvaluativeStoppingCriterion - Class in geneticWedge.gp
An EvaluativeStoppingCriterion checks some property of the fitness function to decide whether evolution should be stopped.
EvaluativeStoppingCriterion() - Constructor for class geneticWedge.gp.EvaluativeStoppingCriterion
 
evolutionNumber - Variable in class geneticWedge.gp.Population
 
evolve(boolean, double[][], double[], double[][], double[], StoppingCriterion) - Method in class geneticWedge.gp.DemicPopulation
If this method is called, the selection method will be deduced from the value of steadyState.
evolve(boolean, AbstractPopulation.SelectionMethod, double[][], double[], double[][], double[], StoppingCriterion) - Method in class geneticWedge.gp.DemicPopulation
DemicPopulation is designed to be used with tournament selection in steady state mode.
evolve(boolean, double[][], double[], double[][], double[], StoppingCriterion) - Method in class geneticWedge.gp.Population
If this method is called, the selection method will be deduced from the value of steadyState.
evolve(boolean, AbstractPopulation.SelectionMethod, double[][], double[], double[][], double[], StoppingCriterion) - Method in class geneticWedge.gp.Population
If this method is called in steadyState mode with a selectMethod that uses roulette wheel selection (FITNESS_PROPORTIONAL, RANK or FUSS), elitist selection will not occur, even if an elite size has been set.
evolve(boolean, AbstractPopulation.SelectionMethod, double[][], double[], double[][], double[], StoppingCriterion) - Method in class geneticWedge.gp.PopulationV
If this method is called in steadyState mode with a selectMethod that uses roulette wheel selection (FITNESS_PROPORTIONAL, RANK or FUSS), elitist selection will not occur, even if an elite size has been set.
evolveOneGeneration(boolean, AbstractPopulation.SelectionMethod, double[][], double[]) - Method in class geneticWedge.gp.DemicPopulation
 
evolveOneGeneration(boolean, AbstractPopulation.SelectionMethod, double[][], double[]) - Method in class geneticWedge.gp.Population
 
ExcelReader - Class in geneticWedge.gp.io
This class contains static methods for reading data from Excel files and returning NumericData objects.
ExcelReader() - Constructor for class geneticWedge.gp.io.ExcelReader
 
ExponentialFunction - Class in geneticWedge.gp.function
ExponentialFunction is a Function that takes 1 input and outputs e^x as its output
ExponentialFunction() - Constructor for class geneticWedge.gp.function.ExponentialFunction
constructor

F

fatalError(SAXParseException) - Method in class geneticWedge.gp.io.XMLTreeHandler
Report a fatal XML parsing error.
fireGen() - Method in class geneticWedge.gp.PopulationV
 
fitnessFunction - Variable in class geneticWedge.gp.AbstractPopulation
The FitnessFunction used to evaluate Individuals.
FitnessShare - Class in geneticWedge.gp
The use of a FitnessShare object encourages diversity within a population.
FitnessShare(double, FitnessShare.FitnessShareFunction) - Constructor for class geneticWedge.gp.FitnessShare
Creates a FitnessShare with a niche size and a FitnessShareFunction.
FitnessShare.FitnessShareFunction - Enum in geneticWedge.gp
FitnessShareFunction determines the shape of the fitness sharing within a niche.
FitnessShare.ShareType - Enum in geneticWedge.gp
ShareType determines the function over which sharing is performed
FitnessStoppingCriterion - Class in geneticWedge.gp
A FitnessStoppingCriterion stops evolution based on some property of the FitnessFunction.
FitnessStoppingCriterion(double, boolean, boolean) - Constructor for class geneticWedge.gp.FitnessStoppingCriterion
Default constructor
FixedGenerationsStoppingCriterion - Class in geneticWedge.gp
If a FixedGenerationsStoppingCriterion is used, early stopping will not occur.
FixedGenerationsStoppingCriterion(int) - Constructor for class geneticWedge.gp.FixedGenerationsStoppingCriterion
Default constructor sets the number of generations for which to evolve.
Function - Class in geneticWedge.gp.function
The abstract parent of all Functions.
Function() - Constructor for class geneticWedge.gp.function.Function
 

G

generationNumber - Variable in class geneticWedge.gp.AbstractPopulation
The number of generations of evolution that have occurred
geneticWedge.gp - package geneticWedge.gp
Provides basic Genetic Programming classes, in particular the Population and Individual classes, which represent a population of solutions and the tree-structured solutions within a population.
geneticWedge.gp.dataAnalysis - package geneticWedge.gp.dataAnalysis
Carries out data analysis, such as calculation of standard deviation, mean, etc.
geneticWedge.gp.demo - package geneticWedge.gp.demo
Contains demo classes to illsutrate the operation of the geneticWedge package.
geneticWedge.gp.display - package geneticWedge.gp.display
Contains classes that display tree-representations of Individuals.
geneticWedge.gp.events - package geneticWedge.gp.events
Package that deals with 'events', allowing real-time interaction with the geneticWedge package.
geneticWedge.gp.function - package geneticWedge.gp.function
Contains classes that represent primitive functions such as +, sin, pow.
geneticWedge.gp.io - package geneticWedge.gp.io
Package deals with reading and writing data for use in genetic programming.
geneticWedge.gp.postProcess - package geneticWedge.gp.postProcess
Contains classes that carry out processing on data after an evolutionary run.
getAbsoluteError(double[][], double[]) - Method in class geneticWedge.gp.Individual
Returns the Absolute Error for the provided dataset.
getAbsoluteError(double[], double) - Method in class geneticWedge.gp.Individual
Returns the absolute error for the single data-point provided.
getAllClassificationData(double[][], double[], double, boolean, boolean) - Method in class geneticWedge.gp.Individual
This returns an array containing 4 values - True Positives, False Positives, True Negatives and False Negatives.
getAllClassificationData(double[][], double) - Static method in class geneticWedge.gp.postProcess.PostProcessor
getAllClassificationData returns the numbers of true positives, false positives, true negatives and false negatives, given a data array and a threshold (cut-off).
getAllCutDepthCorrelations() - Method in class geneticWedge.gp.Population
This method may be used if transmission information has been collected.
getAllFitnesses(String, boolean) - Static method in class geneticWedge.gp.postProcess.PostProcessor
getAllFitnesses returns the training, validation and test fitnesses for the 'best' individual, selected on validation fitness.
getAllFitnesses(String, boolean, PostProcessor.SELECT_MODE) - Static method in class geneticWedge.gp.postProcess.PostProcessor
getAllFitnesses returns the training, validation and test fitnesses for the 'best' individual, selected using the criterion mode.
getAllowCombinedOp() - Method in class geneticWedge.gp.PopulationDescriptor
Returns allowCombinedOp.
getAllRECCoordinates(double[][], double[], AbstractPopulation.FitnessFunction) - Method in class geneticWedge.gp.Individual
This method ia used in calculateing AOREC values.
getAllROCCoordinates(double[][], double[]) - Method in class geneticWedge.gp.Individual
This method is used in calculating AUROC values.
getAllROCCoordinates(double[], double[]) - Method in class geneticWedge.gp.Individual
This method is used in calculating AUROC values.
getAllROCCoordinates(double[], double[]) - Static method in class geneticWedge.gp.Utils
This method is used in calculating AUROC values.
getAllRSquared(String, PostProcessor.SELECT_MODE) - Static method in class geneticWedge.gp.postProcess.PostProcessor
getAllRSquared returns an array containing R-squared values (Pearson coefficients) for training, validation and test data.
getAllSquaredDistances(boolean) - Method in class geneticWedge.gp.Population
Returns a 2-D array containing the 'distances' between pairs of Individuals, in the 'upper right' sector (above the leading diagonal).
getAOREC(double[][], double[], int, AbstractPopulation.FitnessFunction) - Method in class geneticWedge.gp.Individual
Returns the Area over the REC curve (AOREC) during a regression task.
getAOREC(double[][], double[], int, AbstractPopulation.FitnessFunction, boolean) - Method in class geneticWedge.gp.Individual
Returns the Area over the REC curve (AOREC) during a regression task.
getAOREC(double[][], double[], AbstractPopulation.FitnessFunction) - Method in class geneticWedge.gp.Individual
Returns the Area over the REC curve (AOREC) during a regression task.
getAOREC(double[][], double[], AbstractPopulation.FitnessFunction, boolean) - Method in class geneticWedge.gp.Individual
Returns the Area over the REC curve (AOREC) during a regression task.
getAUROC(double[][], double[], int) - Method in class geneticWedge.gp.Individual
Returns the Area under the ROC curve (AUROC) during a classification task.
getAUROC(double[][], double[], int, boolean, boolean) - Method in class geneticWedge.gp.Individual
Returns the Area under the ROC curve (AUROC) during a classification task.
getAUROC(double[][], double[]) - Method in class geneticWedge.gp.Individual
Calculates and returns the Area under the ROC curve (AUROC) during a classification task, using all of the provided data.
getAUROC(double[][], double[], boolean, boolean) - Method in class geneticWedge.gp.Individual
Calculates and returns the Area under the ROC curve (AUROC) during a classification task, using all of the provided data.
getAUROC(double[], double[]) - Static method in class geneticWedge.gp.Utils
Calculates and returns the Area under the ROC curve (AUROC) during a classification task, using all of the provided data.
getAUROCSampleSize() - Method in class geneticWedge.gp.AbstractPopulation
AUROC sample size is also used for REC curves and Combined Classification Error.
getAverageComplexity() - Method in class geneticWedge.gp.Population
Returns the average function complexity of all Individuals within the population.
getAverageCutDepthCorrelation() - Method in class geneticWedge.gp.Population
This method may be used if transmission information has been collected.
getAverageFitness(double[][], double[], boolean) - Method in class geneticWedge.gp.Population
Returns the average fitness of all Individual on the data provided.
getAverageIndividualLength() - Method in class geneticWedge.gp.Population
Returns the average length (number of nodes) of all Individuals in this Population.
getAverageSquaredDistance(int) - Method in class geneticWedge.gp.Population
Returns the average squared distance between the Individual denoted by index and all other members of the population.
getAverageSquaredDistance(int, Individual) - Method in class geneticWedge.gp.Population
Obtains the average distance that would occur if the new Individual were to replace the Individual currently at index index.
getAverageSquaredDistance(Individual) - Method in class geneticWedge.gp.Population
Obtains the average distance between ind and the Population's current members
getAverageTrainingFitness() - Method in class geneticWedge.gp.AbstractPopulation
Returns the average fitness of all Individuals on the training data.
getAverageTrainingFitness() - Method in class geneticWedge.gp.Population
Returns the average fitness of all Individuals on the training data.
getAverageValidationFitness() - Method in class geneticWedge.gp.AbstractPopulation
Returns the average fitness of all Individuals on the validation data.
getAverageValidationFitness() - Method in class geneticWedge.gp.Population
Returns the average fitness of all Individuals on the validation data.
getBestIndividual() - Method in class geneticWedge.gp.events.GPGenerationEvent
 
getBestIndividual() - Method in class geneticWedge.gp.Population
Returns the best Individual on the training data.
getBestIndividualAsString(String, boolean, PostProcessor.SELECT_MODE) - Static method in class geneticWedge.gp.postProcess.PostProcessor
getBestIndividualAsString returns the 'best' individual as a string, containing all nodes as a comma-separated list.
getBestProgramLengthFromFile(String, String, boolean) - Static method in class geneticWedge.gp.dataAnalysis.DataAcquirer
This method returns the length of the best Individual within a Population, as represented within a results file.
getBestROCThreshold(double[][], double[]) - Method in class geneticWedge.gp.Individual
This method returns the threshold value that results in the point on the ROC closest to (0,1).
getBestROCThreshold(double[], double[]) - Method in class geneticWedge.gp.Individual
This method returns the threshold value that results in the point on the ROC closest to (0,1).
getBestROCThreshold(double[][], double[], boolean) - Method in class geneticWedge.gp.Individual
If useCachedValue is true, inputs and targetOutputs will only be used if a cached value is not available.
getBestTrainingFitness() - Method in class geneticWedge.gp.AbstractPopulation
Returns the fitness of the best Individual on the training data.
getBestTrainingFitness() - Method in class geneticWedge.gp.events.GPGenerationEvent
 
getBestTrainingFitness() - Method in class geneticWedge.gp.Population
Returns the fitness of the best Individual on the training data.
getBestValidatedIndividual() - Method in class geneticWedge.gp.Population
This method will return null if no evolution has occurred (because no validation has been performed) or if a validation set was not provided or a validation criterion was not used.
getBestValidationAndTestFitness(String, boolean) - Static method in class geneticWedge.gp.postProcess.PostProcessor
getBestValidationAndTestFitness returns the validation and test fitnesses for the 'best' individual, selected on validation fitness.
getBestValidationFitness() - Method in class geneticWedge.gp.AbstractPopulation
Returns the fitness of the best Individual on the validation data.
getBestValidationfitness() - Method in class geneticWedge.gp.events.GPGenerationEvent
 
getBestValidationFitness() - Method in class geneticWedge.gp.Population
Returns the fitness of the best Individual on the validation data.
getBroodUse() - Method in class geneticWedge.gp.Crossover
Checks whether brood recombination is being used.
getBroodUse() - Method in class geneticWedge.gp.Population
If set to true, brood recombination will be used during crossover
getCombinedClassificationError(double[][], double[], int, boolean, boolean, boolean) - Method in class geneticWedge.gp.Individual
This is the sqrt of the sum of the squares of the false negative fraction and the false positive fraction during classification.
getCombinedClassificationError(double[][], double[], boolean, boolean, boolean) - Method in class geneticWedge.gp.Individual
This is the sqrt of the sum of the squares of the false negative fraction and the false positive fraction during classification.
getComplexity() - Method in class geneticWedge.gp.function.Function
Should return the complexity of the Function.
getComponents() - Method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the Components available to members of the Population
getConstantMutationStepSize() - Method in class geneticWedge.gp.Mutation
The stepSize determines how far constant values move during CONSTANT mutation.
getConstants() - Method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the Constants available to members of the Population
getConstants() - Method in class geneticWedge.gp.IndividualDescriptor
Returns the array of Constants used by this descriptor
getConstants() - Method in class geneticWedge.gp.PopulationDescriptor
Returns the array of Constants used when constructing a Population.
getCorrelation(double[][]) - Static method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the correlation coefficient (R^2) for 2 variables.
getCrossover() - Method in class geneticWedge.gp.Population
Returns the Crossover object to be used by this Population.
getData() - Method in class geneticWedge.gp.io.NumericData
Returns the data held by this NumericData object.
getData(int[]) - Method in class geneticWedge.gp.io.NumericData
Returns selected data held by this NumericData object.
getData() - Method in class geneticWedge.gp.io.StringData
Returns the data held by this StringData object.
getData(String) - Method in class geneticWedge.gp.io.XMLTreeHandler
This method returns all data identified by the variable name dataName.
getDataLength() - Method in class geneticWedge.gp.io.NumericData
Returns the length of the data.
getDataLength() - Method in class geneticWedge.gp.io.StringData
Returns the number of data items in the dataset.
getDataNames() - Method in class geneticWedge.gp.io.XMLTreeHandler
This method returns the variable names retrieved from the XML file.
getDataSamplingFactor() - Method in class geneticWedge.gp.Crossover
The dataSamplingFactor is a variable related to brood recombination.
getDepth() - Method in class geneticWedge.gp.Individual
Returns the depth of this Individual.
getDepth(Vector<Component>, int) - Static method in class geneticWedge.gp.Utils
This method returns the depth of the node represented by index
getDimensionality() - Method in class geneticWedge.gp.io.NumericData
Returns the dimensionality of the data.
getDimensionality() - Method in class geneticWedge.gp.io.StringData
Returns the dimensionality of the data.
getDimensions() - Method in class geneticWedge.gp.DemicPopulation
Returns the width and length of this population.
getDistance(Individual, Individual) - Static method in class geneticWedge.gp.Utils
This method returns the genotypic distance between 2 Individuals.
getDistance(Vector<Component>, Vector<Component>) - Static method in class geneticWedge.gp.Utils
This method returns the genotypic distance between 2 component lists.
getDiversitiesFromFile(String) - Static method in class geneticWedge.gp.dataAnalysis.DataAcquirer
This method returns the tree diversity and the fitness diversity for a population.
getDiversity() - Method in class geneticWedge.gp.Population
getDiversity() counts the number of different Individuals in the Population, subtracts 1 and divides by (population size - 1).
getEliteSize() - Method in class geneticWedge.gp.PopulationDescriptor
Returns the size of the elite.
getEndOfFragment(Vector<Component>, int) - Static method in class geneticWedge.gp.Utils
This method calculates the index of the last node within a subtree.
getExpandedStringFunction() - Method in class geneticWedge.gp.Individual
Returns the function represented by this Individual, with all terms expanded out and collected.
getFitnesses() - Method in class geneticWedge.gp.Population
This method should only be called after evolving the population.
getFitnessFunction() - Method in class geneticWedge.gp.Population
Returns the FitnessFunction used to evaluate Individuals within this Population.
getFitnessShare() - Method in class geneticWedge.gp.Population
Returns the fitness share object.
getFractionalInputUseFromFile(String) - Static method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the Input use within a population, as represented in a results file.
getFragmentDepths(Vector<Component>, int, int) - Static method in class geneticWedge.gp.Utils
This method calulates the minimum and maximum depths occurring between 2 nodes (those represented by startIndex and endIndex).
getFunctions() - Method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the Functions available to members of the Population
getFunctions() - Method in class geneticWedge.gp.IndividualDescriptor
Returns the array of Functions used by this descriptor
getFunctions() - Method in class geneticWedge.gp.PopulationDescriptor
Returns the array of Functions used when constructing a Population.
getFunctionUseFromFile(String) - Static method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the Function use within a population, as represented in a results file.
getGenerationNumber() - Method in class geneticWedge.gp.AbstractPopulation
Returns the number of generations of evolution that have occurred.
getGenerationNumber() - Method in class geneticWedge.gp.events.GPGenerationEvent
 
getGrowFunctionProportion() - Method in class geneticWedge.gp.Individual
Returns the probability of a node selected during growth being a Function (rather than a Terminal).
getGrowFunctionProportion() - Method in class geneticWedge.gp.IndividualDescriptor
Returns the growFunctionProportion used by this descriptor.
getGrowFunctionProportion() - Method in class geneticWedge.gp.PopulationDescriptor
Returns the growFunctionProportion used when constructing a Population.
getGrowMethod() - Method in class geneticWedge.gp.IndividualDescriptor
Returns the method that will be used to grow Individuals, i.e.
getGrowMethod() - Method in class geneticWedge.gp.PopulationDescriptor
Returns the PopulationGrowMethod used when constructing a Population.
getHalfBroodSize() - Method in class geneticWedge.gp.Crossover
halfBroodSize is the number of pairs of offspring created during brood recombination.
getIndicesProbabilistically(Vector<Integer>, boolean) - Static method in class geneticWedge.gp.Utils
This method takes a vector of indices that are assumed to be ordered.
getIndicesProbabilistically(int[], boolean) - Static method in class geneticWedge.gp.Utils
This method takes a vector of indices that are assumed to be ordered.
getIndividualFromString(String, Function[], Input[], Constant[]) - Static method in class geneticWedge.gp.Individual
 
getIndividuals() - Method in class geneticWedge.gp.Population
 
getInitialPopulationSize() - Method in class geneticWedge.gp.AbstractPopulation
Returns the initial population size.
getInitialSelectionPressure() - Method in class geneticWedge.gp.PopulationDescriptor
 
getInputs() - Method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the Inputs available to members of the Population
getInputs() - Method in class geneticWedge.gp.IndividualDescriptor
Returns the array of Inputs used by this descriptor
getInputs() - Method in class geneticWedge.gp.PopulationDescriptor
Returns the array of Inputs used when constructing a Population.
getInputUseFromFile(String) - Static method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the Input use within a population, as represented in a results file.
getKeepDominated() - Method in class geneticWedge.gp.Population
If set to true, the Population size will be maintained when using a multi-objective evaluation function (PerformanceFunctions).
getLabels() - Method in class geneticWedge.gp.io.NumericData
Returns the data 'labels' held by this NumericData object.
getLabels() - Method in class geneticWedge.gp.io.StringData
Returns the data labels of the data.
getLength() - Method in class geneticWedge.gp.Individual
Returns the length (number of nodes) in this Individual.
getMaxGenerations() - Method in class geneticWedge.gp.AbstractPopulation
Returns the maximum number of generations for which the population may evolve.
getMaximumExpandDepth() - Method in class geneticWedge.gp.Mutation
maximumExpandDepth is the maximum allowable depth of the subtree grown during an EXPAND mutation.
getMaximumIndividualDepth() - Method in class geneticWedge.gp.Population
Retruns the maximum depth of an Individual created by crossover or mutation.
getMaximumIndividualLength() - Method in class geneticWedge.gp.Population
Returns the maximum length of an Individual created by crossover or mutation.
getMaximumReplacementDepth() - Method in class geneticWedge.gp.Mutation
maximumReplacementDepth is the maximum allowable depth of the subtree grown during a SUBTREE mutation.
getMaxTreeDepth() - Method in class geneticWedge.gp.IndividualDescriptor
Returns the maximum depth of trees grown using this descriptor.
getMaxTreeDepth() - Method in class geneticWedge.gp.PopulationDescriptor
Returns the maximum tree depth used when constructing a Population.
getMean(double[]) - Static method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the mean value of a set of data.
getMedian(double[]) - Static method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the median value of a set of data.
getMessage() - Method in exception geneticWedge.gp.IllegalMutationReproductionRatesException
 
getMessage() - Method in exception geneticWedge.gp.InvalidFractionException
 
getMessage() - Method in exception geneticWedge.gp.InvalidInputSizeException
 
getMessage() - Method in exception geneticWedge.gp.InvalidRangeException
 
getMinMax(double[]) - Static method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the minimum and maximum values of a dataset.
getMinTreeDepth() - Method in class geneticWedge.gp.IndividualDescriptor
Returns the minimum depth of trees grown using this descriptor.
getMinTreeDepth() - Method in class geneticWedge.gp.PopulationDescriptor
Returns the minimum tree depth used when constructing a Population.
getModificationPointFromPoissonDistribution(double, boolean) - Method in class geneticWedge.gp.Individual
lambda should be a number between 0.0 and 1.0, i.e.
getModificationPointFromPoissonDistribution(double, Vector<Integer>, boolean) - Method in class geneticWedge.gp.Individual
lambda should be a number between 0.0 and 1.0, i.e.
getMSE(double[][], double[]) - Method in class geneticWedge.gp.Individual
Returns the Mean Square Error for the provided dataset.
getMultiObjective() - Method in class geneticWedge.gp.Population
If true, and PerformanceFunctions have been applied, multi-objective (Pareto-style) selection will occur.
getMutatedConstants() - Method in class geneticWedge.gp.PopulationDescriptor
When CONSTANT_VALUE mutation is included as a mutation operation, new Constant objects may be created.
getMutation() - Method in class geneticWedge.gp.Population
Returns the Mutation object to be used by this Population.
getMutationOperators() - Method in class geneticWedge.gp.Mutation
Returns the array of mutationOperators used to perform mutation.
getMutationProportion() - Method in class geneticWedge.gp.PopulationDescriptor
Returns the probability of mutation occurring during the creation of offspring.
getNames() - Method in class geneticWedge.gp.io.NumericData
Returns the variable names held by this NumericData object.
getNames() - Method in class geneticWedge.gp.io.StringData
Returns the variable names of the data.
getNegativePredictiveValue(double[][], double[]) - Method in class geneticWedge.gp.Individual
Returns the Negative Predictive Value (NPV) during a classification task.
getNegativePredictiveValue(double[][], double[], double) - Method in class geneticWedge.gp.Individual
Returns the Negative Predictive Value (NPV) during a classification task.
getNicheSize() - Method in class geneticWedge.gp.FitnessShare
Returns the niche size (radius).
getNodes() - Method in class geneticWedge.gp.Individual
Returns the Components within this Individual in the correct order, working from root to leaf and left to right.
getNoOfInputs() - Method in class geneticWedge.gp.function.Function
Should return the length of the array required by getOutput()
getNumberCorrectBinary(double[][], double[]) - Method in class geneticWedge.gp.Individual
Returns the number of correctly classified outputs from the provided dataset.
getNumberCorrectBinary(double[][], double[], double) - Method in class geneticWedge.gp.Individual
Returns the number of correctly classified outputs from the provided dataset.
getNumberedInputs(Hashtable<String, Double>[], String[]) - Static method in class geneticWedge.gp.Utils
 
getNumericIndices() - Method in class geneticWedge.gp.io.StringData
This method checks which columns of the data contain numeric data.
getOutput(double[]) - Method in class geneticWedge.gp.function.AdditionFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 2.
getOutput(double[]) - Method in class geneticWedge.gp.function.ANDFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 2.
getOutput(double[]) - Method in class geneticWedge.gp.function.BipolarSigmoidFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 1.
getOutput(double[]) - Method in class geneticWedge.gp.function.CosineFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 1.
getOutput(double[]) - Method in class geneticWedge.gp.function.DivisionFunction
This method performs protected division.
getOutput(double[]) - Method in class geneticWedge.gp.function.ExponentialFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 1.
getOutput(double[]) - Method in class geneticWedge.gp.function.Function
All non-abstract subclasses must implement this method, so that they can transform inputs into a single output.
getOutput(double[]) - Method in class geneticWedge.gp.function.GREATER_THAN_EQUAL_ZEROFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 1.
getOutput(double[]) - Method in class geneticWedge.gp.function.GREATER_THAN_ZEROFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 1.
getOutput(double[]) - Method in class geneticWedge.gp.function.IdentityFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 1.
getOutput(double[]) - Method in class geneticWedge.gp.function.IFFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 1.
getOutput(double[]) - Method in class geneticWedge.gp.function.InverseFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 1.
getOutput(double[]) - Method in class geneticWedge.gp.function.LESS_THAN_EQUAL_ZEROFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 1.
getOutput(double[]) - Method in class geneticWedge.gp.function.LESS_THAN_ZEROFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 1.
getOutput(double[]) - Method in class geneticWedge.gp.function.LogFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 1.
getOutput(double[]) - Method in class geneticWedge.gp.function.MaxFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 2.
getOutput(double[]) - Method in class geneticWedge.gp.function.MinFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 2.
getOutput(double[]) - Method in class geneticWedge.gp.function.MultiplicationFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 2.
getOutput(double[]) - Method in class geneticWedge.gp.function.NANDFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 2.
getOutput(double[]) - Method in class geneticWedge.gp.function.NOTFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 1.
getOutput(double[]) - Method in class geneticWedge.gp.function.ORFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 2.
getOutput(double[]) - Method in class geneticWedge.gp.function.PowerFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 2.
getOutput(double[]) - Method in class geneticWedge.gp.function.SineFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 1.
getOutput(double[]) - Method in class geneticWedge.gp.function.SqrtFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 1.
getOutput(double[]) - Method in class geneticWedge.gp.function.SubtractionFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 2.
getOutput(double[]) - Method in class geneticWedge.gp.function.TanFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 1.
getOutput(double[]) - Method in class geneticWedge.gp.function.UnipolarSigmoidFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 1.
getOutput(double[]) - Method in class geneticWedge.gp.function.XORFunction
getOutput() throws InvalidInputSizeException if the length of the input array is not 2.
getOutput(double[]) - Method in class geneticWedge.gp.Individual
Returns the output of this Individual, given the provided input vector.
getOutputClasses(String[]) - Static method in class geneticWedge.gp.Utils
Returns the unique classes avaialable from a list of class memberships, sorted into ascending (alphabetical) order.
getPanelSize() - Method in class geneticWedge.gp.display.TreePanel
 
getPerformanceFunctions() - Method in class geneticWedge.gp.Population
Returns an array of the PerformanceFunctions used in selecting Individuals.
getPoissonDistribution(double, int, int) - Static method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns a Poisson distribution as a set of probabilities of values between min and max.
getPopulationDescriptor() - Method in class geneticWedge.gp.AbstractPopulation
Returns a Population Descriptor object, which holds information concerning the Population as a whole.
getPopulationSize() - Method in class geneticWedge.gp.AbstractPopulation
Returns the current population size.
getPositivePredictiveValue(double[][], double[]) - Method in class geneticWedge.gp.Individual
Returns the Positive Predictive Value (PPV) during a classification task.
getPositivePredictiveValue(double[][], double[], double) - Method in class geneticWedge.gp.Individual
Returns the Positive Predictive Value (PPV) during a classification task.
getProgramLengthsFromFile(String, String) - Static method in class geneticWedge.gp.dataAnalysis.DataAcquirer
This method returns the lengths of all Individuals within a Population, as represented within a results file.
getRandomIndices(int, int) - Static method in class geneticWedge.gp.Utils
Returns an array containing numberOfIndices.
getRandomIndices(int) - Static method in class geneticWedge.gp.Utils
Returns the integers between 1 and length (inclusive) in random order.
getRankGradient() - Method in class geneticWedge.gp.Population
Returns the rank gradient to be used during RANK selection.
getRECCoordinates(double[][], double[], int, AbstractPopulation.FitnessFunction) - Method in class geneticWedge.gp.Individual
This method ia used in calculateing AOREC values.
getRECFitnessFunction() - Method in class geneticWedge.gp.AbstractPopulation
Returns the FitnessFunction to be used when constructing a REC curve.
getReproductionProportion() - Method in class geneticWedge.gp.PopulationDescriptor
Returns the probability of reproduction (cloning) occurring during the creation of offspring.
getRMSE(double[][], double[]) - Method in class geneticWedge.gp.Individual
Returns the Root Mean Square Error for the provided dataset.
getROCCoordinates(double[][], double[], int) - Method in class geneticWedge.gp.Individual
This method is used in calculateing AUROC values.
getScalarData(DataAcquirer.ScalarData) - Method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the required ScalarData for all Individuals within the Population
getScalarData(DataAcquirer.ScalarData[], int) - Method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the required ScalarData for all Individuals within the Population.
getSensitivity(double[][], double[]) - Method in class geneticWedge.gp.Individual
Returns the sensitivity during a classification task.
getSensitivity(double[][], double[], double) - Method in class geneticWedge.gp.Individual
Returns the sensitivity during a classification task.
getShareType() - Method in class geneticWedge.gp.Population
Returns the fitness type.
getShareValuesFromMultipleObjectives(double[][], double[]) - Method in class geneticWedge.gp.FitnessShare
This method takes weightings for a multi-objective function as the second input.
getShareValuesFromSingleObjective(double[]) - Method in class geneticWedge.gp.FitnessShare
Returns the share values (degree of sharing) for the data provided.
getShareValuesFromSingleObjective(double[], int) - Method in class geneticWedge.gp.FitnessShare
Returns the share value (degree of sharing) for the particular datum identified by index.
getShareValuesFromSquaredDistances(double[][]) - Method in class geneticWedge.gp.FitnessShare
Returns the share values (degree of sharing) for the squared distances provided.
getShareValuesFromSquaredDistances(double[][], int) - Method in class geneticWedge.gp.FitnessShare
Returns the share value (degree of sharing) for the particular datum identified by index.
getShareWeightings() - Method in class geneticWedge.gp.Population
Returns the share weightings.
getSpecificity(double[][], double[]) - Method in class geneticWedge.gp.Individual
Returns the specificity during a classification task.
getSpecificity(double[][], double[], double) - Method in class geneticWedge.gp.Individual
Returns the specificity during a classification task.
getSquaredDistances(int[], boolean) - Method in class geneticWedge.gp.Population
Returns the distances between selected Individuals in the Population, denoted by their indices, and all other members of the Population.
getSquaredError(double[], double) - Method in class geneticWedge.gp.Individual
Returns the square of the error for the single data-point provided.
getStandardDeviation(double[]) - Static method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the standard deviation of a set of data.
getTerminalSubtreesFromFile(String) - Static method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the terminal subtree use within a population, as represented in a results file.
getThresholdAdjustedOutput(double[]) - Method in class geneticWedge.gp.Individual
Returns the threshold adjusted error, i.e.
getTournamentSize() - Method in class geneticWedge.gp.AbstractPopulation
Returns the tournament size to be used during tournament selection.
getTransmissionInfo() - Method in class geneticWedge.gp.Crossover
Returns a vector containing information about the relationship between parent and offspring during crossover operations, provided collectTransmissionInfo has been set to true.
getTransmissionInfo() - Method in class geneticWedge.gp.Mutation
Returns a vector containing information about the relationship between parent and offspring during mutation operations, provided collectTransmissionInfo has been set to true.
getTransmissionInfo() - Method in class geneticWedge.gp.Population
Returns a vector containing transmission information concerning the relationships between parents and offspring
getValue() - Method in class geneticWedge.gp.Constant
Returns the value output by this Constant object.
getValue() - Method in class geneticWedge.gp.Terminal
Returns the value of this Terminal
getVariance(double[]) - Static method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the variance of a set of data.
getVectorData(DataAcquirer.VectorData, DataAcquirer.ScalarData) - Method in class geneticWedge.gp.dataAnalysis.DataAcquirer
Returns the requested VectorData for all Individuals within the Population.
getVectorData(DataAcquirer.VectorData) - Method in class geneticWedge.gp.dataAnalysis.DataAcquirer
This method returns data for the Individuals in the same order as in the population.
GPDone(GPDoneEvent) - Method in interface geneticWedge.gp.events.GPEventHandler
 
GPDoneEvent - Class in geneticWedge.gp.events
 
GPDoneEvent(Object) - Constructor for class geneticWedge.gp.events.GPDoneEvent
 
GPEventHandler - Interface in geneticWedge.gp.events
 
GPGeneration(GPGenerationEvent) - Method in interface geneticWedge.gp.events.GPEventHandler
 
GPGenerationEvent - Class in geneticWedge.gp.events
 
GPGenerationEvent(Object) - Constructor for class geneticWedge.gp.events.GPGenerationEvent
 
GREATER_THAN_EQUAL_ZEROFunction - Class in geneticWedge.gp.function
A unary function that returns +1 if its input is greater than or equal to zero, -1 otherwise.
GREATER_THAN_EQUAL_ZEROFunction() - Constructor for class geneticWedge.gp.function.GREATER_THAN_EQUAL_ZEROFunction
constructor
GREATER_THAN_ZEROFunction - Class in geneticWedge.gp.function
A unary function that returns +1 if its input is greater than zero, -1 otherwise.
GREATER_THAN_ZEROFunction() - Constructor for class geneticWedge.gp.function.GREATER_THAN_ZEROFunction
constructor

H

hasNoDiversity() - Method in class geneticWedge.gp.Population
 

I

IdentityFunction - Class in geneticWedge.gp.function
IdentityFunction passes on a unary input unchanged
IdentityFunction() - Constructor for class geneticWedge.gp.function.IdentityFunction
constructor
IFFunction - Class in geneticWedge.gp.function
IFFunction is a unary function that returns +1 if the input is greater than 0, -1 otherwise.
IFFunction() - Constructor for class geneticWedge.gp.function.IFFunction
constructor
IllegalMutationReproductionRatesException - Exception in geneticWedge.gp
This Exception is thrown if mutation or reproduction rates are set outside the range [0,1].
IllegalMutationReproductionRatesException() - Constructor for exception geneticWedge.gp.IllegalMutationReproductionRatesException
 
Individual - Class in geneticWedge.gp
The Individual class represents a single tree (program).
Individual(IndividualDescriptor) - Constructor for class geneticWedge.gp.Individual
Constructs an Individual according to parameters held by the IndividualDescriptor.
Individual(IndividualDescriptor.IndividualGrowMethod, int, int, Function[], Input[], Constant[], double) - Constructor for class geneticWedge.gp.Individual
Constructs an Individual from the parameters provided.
Individual(int, Function[], Input[], Constant[], double) - Constructor for class geneticWedge.gp.Individual
Constructs an Individual from the parameters provided, using the GROW method.
Individual(IndividualDescriptor.IndividualGrowMethod, int, int, Function[], Input[], Constant[]) - Constructor for class geneticWedge.gp.Individual
Conctructs an Individual from the parameters provided.
Individual(Vector<Component>, Terminal[]) - Constructor for class geneticWedge.gp.Individual
Constructs a new Individual containing the Components in newNodes in the specified order.
Individual(Vector<Component>, Input[], Constant[]) - Constructor for class geneticWedge.gp.Individual
Constructs a new Individual containing the Components in newNodes in the specified order.
IndividualDescriptor - Class in geneticWedge.gp
IndividualDescriptor holds the information required to create an Individual
IndividualDescriptor(IndividualDescriptor.IndividualGrowMethod, int, Function[], Input[], Constant[]) - Constructor for class geneticWedge.gp.IndividualDescriptor
Creates an IndividualDescriptor with all of the information needed to create a new Individual.
IndividualDescriptor.IndividualGrowMethod - Enum in geneticWedge.gp
Determines whether an Individual is grown by the FULL or GROW method
Input - Class in geneticWedge.gp
A Terminal with a variable value.
Input(String) - Constructor for class geneticWedge.gp.Input
Note: users must ensure that input name is unique, to allow identification of input.
Input(int) - Constructor for class geneticWedge.gp.Input
Note: user must ensure that input number is unique, to allow identification of input
InvalidFractionException - Exception in geneticWedge.gp
This Exception is thrown if an attempt is made to set the GrpwFunctionProportion to a value outside the range [0,1].
InvalidFractionException() - Constructor for exception geneticWedge.gp.InvalidFractionException
 
InvalidInputSizeException - Exception in geneticWedge.gp
This Exception is thrown if an attempt is made to calculate outputs using an inappropriately sized array of inputs.
InvalidInputSizeException() - Constructor for exception geneticWedge.gp.InvalidInputSizeException
 
InvalidRangeException - Exception in geneticWedge.gp
This Exception is thrown if a range of values, such as minimum and maximum tree depths are set inappropriately.
InvalidRangeException() - Constructor for exception geneticWedge.gp.InvalidRangeException
 
InverseFunction - Class in geneticWedge.gp.function
InverseFunction takes a single input and returns the inverse value (1/x).
InverseFunction() - Constructor for class geneticWedge.gp.function.InverseFunction
constructor
isCommutative() - Method in class geneticWedge.gp.function.AdditionFunction
Returns true
isCommutative() - Method in class geneticWedge.gp.function.ANDFunction
Returns true
isCommutative() - Method in class geneticWedge.gp.function.DivisionFunction
Returns false
isCommutative() - Method in class geneticWedge.gp.function.MaxFunction
Returns true
isCommutative() - Method in class geneticWedge.gp.function.MinFunction
Returns true
isCommutative() - Method in class geneticWedge.gp.function.MultiplicationFunction
Returns true
isCommutative() - Method in class geneticWedge.gp.function.NANDFunction
Returns true
isCommutative() - Method in class geneticWedge.gp.function.ORFunction
Returns true
isCommutative() - Method in class geneticWedge.gp.function.PowerFunction
Returns false
isCommutative() - Method in class geneticWedge.gp.function.SubtractionFunction
Returns false
isCommutative() - Method in class geneticWedge.gp.function.TwoInputFunction
non-abstract subclasses must implement this method.
isCommutative() - Method in class geneticWedge.gp.function.XORFunction
Returns true

L

lastGenerationWasImproved() - Method in class geneticWedge.gp.StagnationStoppingCriterion
Returns true if there was an improvment in evaluation function during creation of the last generation.
LESS_THAN_EQUAL_ZEROFunction - Class in geneticWedge.gp.function
A unary function that returns +1 if its input is less than or equal to zero, -1 otherwise.
LESS_THAN_EQUAL_ZEROFunction() - Constructor for class geneticWedge.gp.function.LESS_THAN_EQUAL_ZEROFunction
constructor
LESS_THAN_ZEROFunction - Class in geneticWedge.gp.function
A unary function that returns +1 if its input is less than zero, -1 otherwise.
LESS_THAN_ZEROFunction() - Constructor for class geneticWedge.gp.function.LESS_THAN_ZEROFunction
constructor
LogFunction - Class in geneticWedge.gp.function
A unary function that returns the natural logarithm of the absolute value of the input
LogFunction() - Constructor for class geneticWedge.gp.function.LogFunction
constructor

M

main(String[]) - Static method in class geneticWedge.gp.demo.DemoUtils
 
main(String[]) - Static method in class geneticWedge.gp.demo.TestClassification
 
main(String[]) - Static method in class geneticWedge.gp.demo.TestGP
 
main(String[]) - Static method in class geneticWedge.gp.demo.TestMultiObjective
 
main(String[]) - Static method in class geneticWedge.gp.demo.TestTrigonometry
 
main(String[]) - Static method in class geneticWedge.gp.display.DisplayTree
 
MaxFunction - Class in geneticWedge.gp.function
MaxFunction is a Function that takes 2 inputs and outputs the larger of the two.
MaxFunction() - Constructor for class geneticWedge.gp.function.MaxFunction
constructor
maxGenerations - Variable in class geneticWedge.gp.AbstractPopulation
The maximum number of generations of evolution that may occur
MinFunction - Class in geneticWedge.gp.function
MinFunction is a Function that takes 2 inputs and outputs the lesser of the two.
MinFunction() - Constructor for class geneticWedge.gp.function.MinFunction
constructor
MultiplicationFunction - Class in geneticWedge.gp.function
MultiplicationFunction is a Function that takes 2 inputs and outputs their product as an output.
MultiplicationFunction() - Constructor for class geneticWedge.gp.function.MultiplicationFunction
constructor
mutate(Individual, int, int, PopulationDescriptor) - Method in class geneticWedge.gp.Mutation
Perform a random mutation on an Individual.
Mutation - Class in geneticWedge.gp
Mutation mutates an Individual using a selection of mutation operators.
Mutation(Mutation.MutationOperator[]) - Constructor for class geneticWedge.gp.Mutation
The constructor takes a list of mutation operations to be used.
Mutation.MutationOperator - Enum in geneticWedge.gp
Mutation operators should be chosen with care.

N

NANDFunction - Class in geneticWedge.gp.function
A binary function that returns -1 if both inputs are greater than zero, 1 otherwise.
NANDFunction() - Constructor for class geneticWedge.gp.function.NANDFunction
constructor
normaliseData() - Method in class geneticWedge.gp.io.NumericData
Returns the data held by this object, normalised to the range [-1,1]
normaliseData(double, double) - Method in class geneticWedge.gp.io.NumericData
Returns the data held by this object, normalised to the range [minVal,maxVal]
normaliseData(int[]) - Method in class geneticWedge.gp.io.NumericData
Returns the values of the data within the variables identified by variableIndices, normalised to the range [-1,1]
normaliseData(double, double, int[]) - Method in class geneticWedge.gp.io.NumericData
Returns the values of the data within the variables identified by variableIndices, normalised to the range [minVal,maxVal]
normaliseData(double[][]) - Method in class geneticWedge.gp.io.NumericData
Normalises newData using the most recently used normalisation factors.
NOTFunction - Class in geneticWedge.gp.function
NOTFunction is a unary function that returns true if its input is less than or equal to zero, -1 otherwise.
NOTFunction() - Constructor for class geneticWedge.gp.function.NOTFunction
constructor
NumericData - Class in geneticWedge.gp.io
This class holds numeric data as well as variable names and data labels.
NumericData(String[], double[][], String[]) - Constructor for class geneticWedge.gp.io.NumericData
constructs a NumericData object with data, variable names and data labels.

O

OneInputFunction - Class in geneticWedge.gp.function
Abstract parent of all unary functions.
OneInputFunction() - Constructor for class geneticWedge.gp.function.OneInputFunction
The constructor sets the number of inputs required to 1
OneInputFunction(int) - Constructor for class geneticWedge.gp.function.OneInputFunction
This constructor allows the creation of Functions with assigned complexity values, rather than the default values.
ORFunction - Class in geneticWedge.gp.function
ORFunction is a Function that takes 2 inputs and outputs +1 if at least one of them is positive, -1 otherwise.
ORFunction() - Constructor for class geneticWedge.gp.function.ORFunction
constructor

P

paintComponent(Graphics) - Method in class geneticWedge.gp.display.TreePanel
 
partitionData(double[], double) - Static method in class geneticWedge.gp.dataAnalysis.DataAcquirer
This method partitions the data into equal sized partitions.
popDescriptor - Variable in class geneticWedge.gp.AbstractPopulation
The PopulationDescriptor that describes this Population
popSize - Variable in class geneticWedge.gp.AbstractPopulation
The current population size.
Population - Class in geneticWedge.gp
Population is the standard Population class.
Population(int, PopulationDescriptor) - Constructor for class geneticWedge.gp.Population
The Population constructor takes the population size and a PopulationDescriptor as variables.
Population.PerformanceFunction - Enum in geneticWedge.gp
PerformanceFunctions are used to create multi-objective evaluation functions.
PopulationDescriptor - Class in geneticWedge.gp
PopulationDescriptor holds the information required to create a Population object.
PopulationDescriptor(PopulationDescriptor.PopulationGrowMethod, int, int, Function[], Input[], Constant[]) - Constructor for class geneticWedge.gp.PopulationDescriptor
Creates a PopulationDescriptor object with a growMethod, minimum and maximum tree depths and arrays of Functions, Constants and Inputs to be used in constructing Individuals.
PopulationDescriptor(PopulationDescriptor.PopulationGrowMethod, int, int, Function[], Input[], Constant[], double) - Constructor for class geneticWedge.gp.PopulationDescriptor
Creates a PopulationDescriptor object with a growMethod, minimum and maximum tree depths, arrays of Functions, Constants and Inputs to be used in constructing Individuals and a growFunctionProportion.
PopulationDescriptor.PopulationGrowMethod - Enum in geneticWedge.gp
PopulationGrowMethod determines the method used to 'grow' the Individuals within a Population
PopulationV - Class in geneticWedge.gp
Extends Population to include the calls to the GPDone & GPGeneration events in the evolve method, and addition of supporting methods.
PopulationV(int, PopulationDescriptor) - Constructor for class geneticWedge.gp.PopulationV
The Population constructor takes the population size and a PopulationDescriptor as variables.
PostProcessor - Class in geneticWedge.gp.postProcess
PostProcessor allows access to various properties after an evolutionary run.
PostProcessor() - Constructor for class geneticWedge.gp.postProcess.PostProcessor
 
PostProcessor.SELECT_MODE - Enum in geneticWedge.gp.postProcess
SELECT_MODE sets the method by which the 'best' individual is selected.
PowerFunction - Class in geneticWedge.gp.function
PowerFunction is a Function that takes 2 inputs and outputs the first raised to the power of the second.
PowerFunction() - Constructor for class geneticWedge.gp.function.PowerFunction
constructor
printInfo - Variable in class geneticWedge.gp.Population
 
ProcessingInstructions(String, String) - Method in class geneticWedge.gp.io.XMLTreeHandler
Receive notification of a processing instruction.

R

randomiseLines(String, String, boolean) - Static method in class geneticWedge.gp.io.TextReader
Randomises the data in the file filename and writes it to the file newFileName.
readFile(String, boolean) - Static method in class geneticWedge.gp.io.CSVReader
Returns a NumericData object by reading a csv file named filename.
readFile(String, String, boolean) - Static method in class geneticWedge.gp.io.TextReader
This method reads data from a file.
readFile(String, String[], String, XMLTreeHandler.IncludeData) - Static method in class geneticWedge.gp.io.XMLDataReader
Returns a NumericData object by reading an xml file located at uri.
readStringFile(String, boolean, boolean) - Static method in class geneticWedge.gp.io.CSVReader
Returns a StringData object by reading a csv file named filename.
readStringFile(String, String, boolean, boolean) - Static method in class geneticWedge.gp.io.TextReader
Returns a StringData object by reading a file named filename.
readWorksheet(String, String, boolean) - Static method in class geneticWedge.gp.io.ExcelReader
This method reads all of the data in worksheet, within spreadsheet.
recFitnessFunction - Variable in class geneticWedge.gp.AbstractPopulation
The FitnessFunction used to evaluate the AOREC.
removeDominatedIndividuals() - Method in class geneticWedge.gp.Population
 
removeDuplicatedIndividuals() - Method in class geneticWedge.gp.Population
 
removeDuplicates(String, String, boolean) - Static method in class geneticWedge.gp.io.CSVReader
Removes duplicated data from the dataset in filename and writes the 'clean' dataset to newFileName.
removeDuplicates(String, String, boolean, String) - Static method in class geneticWedge.gp.io.TextReader
Removes duplicated data from the dataset in filename and writes the 'clean' dataset to newFileName.
removeGPDoneHandler(GPEventHandler) - Method in class geneticWedge.gp.PopulationV
 
removeGPGeneration(GPEventHandler) - Method in class geneticWedge.gp.PopulationV
 
resetMutatedConstants() - Method in class geneticWedge.gp.PopulationDescriptor
When CONSTANT_VALUE mutation is included as a mutation operation, new Constant objects may be created.
ResultWriter - Class in geneticWedge.gp.io
Class for writing standard results files.
ResultWriter() - Constructor for class geneticWedge.gp.io.ResultWriter
 
run() - Method in class geneticWedge.gp.display.UpdateFrame
 

S

savePopulation() - Method in class geneticWedge.gp.Population
 
setAUROCSampleSize(int) - Method in class geneticWedge.gp.AbstractPopulation
AUROC sample size is also used for REC curves and Combined Classification Error.
setBestIndividual(Individual) - Method in class geneticWedge.gp.events.GPGenerationEvent
 
setBestTrainingFitness(double) - Method in class geneticWedge.gp.events.GPGenerationEvent
 
setBestValidationfitness(double) - Method in class geneticWedge.gp.events.GPGenerationEvent
 
setBroodSize(int) - Method in class geneticWedge.gp.Crossover
halfBroodSize is the number of pairs of offspring created during brood recombination.
setBroodSize(int, int) - Method in class geneticWedge.gp.Crossover
halfBroodSize is the number of pairs of offspring created during brood recombination.
setBroodUse(boolean) - Method in class geneticWedge.gp.Crossover
Sets whether brood recombination should be used.
setBroodUse(boolean) - Method in class geneticWedge.gp.Population
If set to true, brood recombination will be used during crossover
setConstantMutationStepSize(double) - Method in class geneticWedge.gp.Mutation
The stepSize determines how far constant values move during CONSTANT mutation.
setCrossover(Crossover) - Method in class geneticWedge.gp.Population
Sets the Crossover object to be used by this Population.
setData(double[][], double[]) - Method in class geneticWedge.gp.Crossover
In order to use brood recombination the data, i.e.
SetDocumentLocator(Locator) - Method in class geneticWedge.gp.io.XMLTreeHandler
Receive a Locator object for document events.
setEliteSize(int) - Method in class geneticWedge.gp.PopulationDescriptor
Sets the size of the elite.
setExpectedCrossoverDepth(double) - Method in class geneticWedge.gp.Crossover
This sets the 'expected' depth at which crossover will take place.
setExpectedMutationDepth(double) - Method in class geneticWedge.gp.Mutation
This sets the 'expected' depth at which mutation will take place.
setFitnessFunction(AbstractPopulation.FitnessFunction) - Method in class geneticWedge.gp.Crossover
This method is only important when using brood recombination.
setFitnessFunction(AbstractPopulation.FitnessFunction) - Method in class geneticWedge.gp.Population
Sets the FitnessFunction used to evaluate Individuals within this Population.
setFitnessShare(FitnessShare, FitnessShare.ShareType) - Method in class geneticWedge.gp.Population
Fitness sharing aims to prevent Individuals within a small niche from dominating the Population.
setFunctionFormat(boolean) - Method in class geneticWedge.gp.io.ResultWriter
Sets the format in which functions will be displayed.
setGenerationNumber(int) - Method in class geneticWedge.gp.events.GPGenerationEvent
 
setGrowFunctionProportion(double) - Method in class geneticWedge.gp.Individual
Sets the probability of a node selected during growth being a Function (rather than a Terminal).
setInitialisationParameters(int) - Method in class geneticWedge.gp.PopulationDescriptor
 
setKeepDominated(boolean) - Method in class geneticWedge.gp.Population
If set to true, the Population size will be maintained when using a multi-objective evaluation function (PerformanceFunctions).
setMaxGenerations(int) - Method in class geneticWedge.gp.AbstractPopulation
Sets the maximum number of generations for which the population may evolve.
setMaximise(boolean) - Method in class geneticWedge.gp.EvaluativeStoppingCriterion
If true, it is assumed that a high-valued FitnessFunction is desirable.
setMaximumExpandDepth(int) - Method in class geneticWedge.gp.Mutation
When the EXPAND mutation takes place, a randomly chosen terminal is replaced by a subtree, grown with the GROW method.
setMaximumIndividualDepth(int) - Method in class geneticWedge.gp.Population
Setting a low maximumIndividualDepth is a way of controlling bloat.
setMaximumIndividualLength(int) - Method in class geneticWedge.gp.Population
Setting a low maximumIndividualLength is a way of controlling bloat.
setMaximumReplacementDepth(int) - Method in class geneticWedge.gp.Mutation
When the SUBTREE_REPLACEMENT mutation takes place, a randomly chosen subtree is replaced by a random subtree, of similar size grown with the GROW method.
setMaxTreeDepth(int) - Method in class geneticWedge.gp.IndividualDescriptor
Sets the maximum depth of trees grown using this descriptor.
setMinTreeDepth(int) - Method in class geneticWedge.gp.IndividualDescriptor
Sets the minimum depth of trees grown using this descriptor.
setMutation(Mutation) - Method in class geneticWedge.gp.Population
Sets the Mutation object to be used by this Population.
setMutationAndReproductionProportions(double, double) - Method in class geneticWedge.gp.PopulationDescriptor
Sets the probabilies of using reproduction (cloning) and mutation operators during evolution.
setMutationAndReproductionProportions(double, double, boolean) - Method in class geneticWedge.gp.PopulationDescriptor
Sets the probabilies of using reproduction (cloning) and mutation operators during evolution.
setMutationProportion(double) - Method in class geneticWedge.gp.PopulationDescriptor
Sets the probability of mutation occurring.
setMutationProportion(double, boolean) - Method in class geneticWedge.gp.PopulationDescriptor
Sets the probability of mutation occurring.
setNicheSize(double) - Method in class geneticWedge.gp.FitnessShare
Sets the niche size (radius).
setPerformanceFunctions(Population.PerformanceFunction[], boolean) - Method in class geneticWedge.gp.Population
Sets the PerformanceFunctions used to evaluate Individuals within this Population.
setPrintStatus(boolean) - Method in class geneticWedge.gp.Population
If printInfo is set to true, Population will print information concerning it's current status to the 'out' stream during evolution.
setRankGradient(double) - Method in class geneticWedge.gp.Population
Sets the rank gradient to be used during RANK selection.
setRECFitnessFunction(AbstractPopulation.FitnessFunction) - Method in class geneticWedge.gp.AbstractPopulation
Sets the FitnessFunction to be used when constructing a REC curve.
setReproductionProportion(double) - Method in class geneticWedge.gp.PopulationDescriptor
Sets the probability of reproduction (cloning) occurring.
setReproductionProportion(double, boolean) - Method in class geneticWedge.gp.PopulationDescriptor
Sets the probability of reproduction (cloning) occurring.
setShareWeightings(double[], boolean) - Method in class geneticWedge.gp.Population
Sets the share weightings.
setSingleObjectiveRatio(double[]) - Method in class geneticWedge.gp.Population
Sets the weightings of performanceFunctions.
setThreshold(int, boolean, double[][]) - Static method in class geneticWedge.gp.postProcess.PostProcessor
 
setThresholdForPPV(double, double[][]) - Static method in class geneticWedge.gp.postProcess.PostProcessor
setThresholdForPPV attamepts to set a threshold (cut-off) value that will yield the desired PPV (positive predictive value).
setTournamentSize(int) - Method in class geneticWedge.gp.AbstractPopulation
Sets the size of the tournament to be used in tournament selection.
setTransmissionWritingParameters(int, String) - Method in class geneticWedge.gp.Population
Sets parameters for saving transmission information (if used).
setTruncationParameters(boolean, int, int) - Method in class geneticWedge.gp.Population
Sets parameters to be used during TRUNCATION selection.
setValue(double) - Method in class geneticWedge.gp.Input
 
ShellSortIndividuals() - Method in class geneticWedge.gp.Population
This method returns an Object array.
ShellSortIndividuals(double[], boolean) - Method in class geneticWedge.gp.Population
This method returns an Object array.
ShellSortIndividuals(Individual[], double[], AbstractPopulation.FitnessFunction) - Static method in class geneticWedge.gp.Population
This method uses the Shell sort algorithm to order an array of Individuals according to theoir fitness.
ShellSortIndividuals(Individual[], double[], boolean) - Static method in class geneticWedge.gp.Population
This method uses the Shell sort algorithm to order an array of Individuals according to theoir fitness.
ShellSortStrings(String[]) - Static method in class geneticWedge.gp.Utils
Sorts values using the Shell sort algorithm, in alphabetical order.
ShellSortValues(double[], boolean) - Static method in class geneticWedge.gp.Utils
Sorts values using the Shell sort algorithm.
ShellSortValues(double[]) - Static method in class geneticWedge.gp.Utils
Sorts values using the Shell sort algorithm, returning them in ascending order.
SineFunction - Class in geneticWedge.gp.function
SineFunction is a Function that takes 1 input and outputs its sine as an output.
SineFunction() - Constructor for class geneticWedge.gp.function.SineFunction
constructor
SqrtFunction - Class in geneticWedge.gp.function
SqrtFunction is a Function that takes 1 input and outputs the square root of its absolute value as the output.
SqrtFunction() - Constructor for class geneticWedge.gp.function.SqrtFunction
constructor
StagnationStoppingCriterion - Class in geneticWedge.gp
StagnationStoppingCriterion stops evolution if no improvement in some measure of Fitness has occurred for some time.
StagnationStoppingCriterion(int, boolean, boolean) - Constructor for class geneticWedge.gp.StagnationStoppingCriterion
StagnationStoppingCriterion constructor.
StagnationStoppingCriterion(int, boolean, boolean, boolean) - Constructor for class geneticWedge.gp.StagnationStoppingCriterion
StagnationStoppingCriterion constructor.
startElement(String, String, String, Attributes) - Method in class geneticWedge.gp.io.XMLTreeHandler
Receive notification of the start of an element.
startingPopSize - Variable in class geneticWedge.gp.AbstractPopulation
The starting population size.
startPrefixMapping(String, String) - Method in class geneticWedge.gp.io.XMLTreeHandler
Receive notification of the start of a Namespace mapping.
stopIfNoDiversity(boolean) - Method in class geneticWedge.gp.StoppingCriterion
If true, evolution will stop prematurely once there is no diversity in the Population (all Individuals are identical).
stopIfNoDiversity() - Method in class geneticWedge.gp.StoppingCriterion
Returns stopOnZeroDiversity.
stopnow() - Method in class geneticWedge.gp.PopulationV
 
StoppingCriterion - Class in geneticWedge.gp
A StoppingCriterion determines when evolution will stop.
StoppingCriterion() - Constructor for class geneticWedge.gp.StoppingCriterion
 
stopReached(AbstractPopulation) - Method in class geneticWedge.gp.FitnessStoppingCriterion
Will return true only if the stop criterion has been reached.
stopReached(AbstractPopulation) - Method in class geneticWedge.gp.FixedGenerationsStoppingCriterion
Returns true if the required number of generations of evolution have occurred.
stopReached(AbstractPopulation) - Method in class geneticWedge.gp.StagnationStoppingCriterion
Returns true if the stopping condition has been reached (no improvement in evaluation function for a fixed number of generations).
stopReached(AbstractPopulation) - Method in class geneticWedge.gp.StoppingCriterion
Absract method that must be implmented by non-absract subclasses.
StringData - Class in geneticWedge.gp.io
This class can extract String data from files and manipulate it in various ways.
StringData(String[], String[][], String[]) - Constructor for class geneticWedge.gp.io.StringData
Constructor takes variable names, data and data labels.
stringToNumericTargets(String[], String[]) - Static method in class geneticWedge.gp.Utils
Converts String representations of class membership into numeric values.
SubtractionFunction - Class in geneticWedge.gp.function
SubtractionFunction is a Function that takes 2 inputs and outputs their difference as an output.
SubtractionFunction() - Constructor for class geneticWedge.gp.function.SubtractionFunction
constructor

T

TanFunction - Class in geneticWedge.gp.function
TanFunction is a Function that takes 1 input and outputs its tangent as an output.
TanFunction() - Constructor for class geneticWedge.gp.function.TanFunction
constructor
Terminal - Class in geneticWedge.gp
Terminal is an abstract class that represents Components that should be used at leaf nodes within a tree (Individual).
Terminal() - Constructor for class geneticWedge.gp.Terminal
 
TestClassification - Class in geneticWedge.gp.demo
 
TestClassification() - Constructor for class geneticWedge.gp.demo.TestClassification
 
TestGP - Class in geneticWedge.gp.demo
This class is a very basic demonstratration of how to use GP to fit to a polynomial (symbolic regression)
TestGP() - Constructor for class geneticWedge.gp.demo.TestGP
 
TestMultiObjective - Class in geneticWedge.gp.demo
 
TestMultiObjective() - Constructor for class geneticWedge.gp.demo.TestMultiObjective
 
TestTrigonometry - Class in geneticWedge.gp.demo
 
TestTrigonometry() - Constructor for class geneticWedge.gp.demo.TestTrigonometry
 
TextReader - Class in geneticWedge.gp.io
This class contains static methods for reading files and returning StringData or NumericData objects.
TextReader() - Constructor for class geneticWedge.gp.io.TextReader
 
toNumericData(int[]) - Method in class geneticWedge.gp.io.StringData
Converts the String data in selected columns into numeric data.
toNumericData(int[], Hashtable<String, Double>) - Method in class geneticWedge.gp.io.StringData
Converts the String data in selected columns into numeric data.
toString() - Method in class geneticWedge.gp.Component
A Component must have a toString() method that allows an Individual to construct a String representation of its components.
toString() - Method in class geneticWedge.gp.Constant
 
toString() - Method in class geneticWedge.gp.FitnessShare
Returns a String representation of this FitnessShare object, identifying its niche size and share function (niche shape)
toString() - Method in class geneticWedge.gp.FitnessStoppingCriterion
Returns a string representation of this FitnessStoppingCriterion.
toString() - Method in class geneticWedge.gp.FixedGenerationsStoppingCriterion
Returns a String representation of this FixedGenerationsStopping Criterion.
toString() - Method in class geneticWedge.gp.function.AdditionFunction
Returns a String representation of an AdditionFunction object ('+').
toString() - Method in class geneticWedge.gp.function.ANDFunction
Returns a String representation of an ANDFunction object ('AND').
toString() - Method in class geneticWedge.gp.function.BipolarSigmoidFunction
Returns a String representation of an BipolarSigmoidFunction object ('BiSig').
toString() - Method in class geneticWedge.gp.function.CosineFunction
Returns a String representation of a CosineFunction object ('cos').
toString() - Method in class geneticWedge.gp.function.DivisionFunction
Returns a String representation of a DivisionFunction object ('÷').
toString() - Method in class geneticWedge.gp.function.ExponentialFunction
Returns a String representation of an ExponentialFunction object ('exp').
toString() - Method in class geneticWedge.gp.function.Function
Returns a String representation of this Function object.
toString() - Method in class geneticWedge.gp.function.GREATER_THAN_EQUAL_ZEROFunction
Returns a String representation of a GREATER_THAN_EQUAL_ZEROFunction object ('>=ZERO').
toString() - Method in class geneticWedge.gp.function.GREATER_THAN_ZEROFunction
Returns a String representation of a GREATER_THAN_ZEROFunction object ('>ZERO').
toString() - Method in class geneticWedge.gp.function.IdentityFunction
Returns a String representation of an IdentityFunction object ('ident').
toString() - Method in class geneticWedge.gp.function.IFFunction
Returns a String representation of an IFFunction object ('IF').
toString() - Method in class geneticWedge.gp.function.InverseFunction
Returns a String representation of an InverseFunction object ('inv').
toString() - Method in class geneticWedge.gp.function.LESS_THAN_EQUAL_ZEROFunction
Returns a String representation of a LESS_THAN_EQUAL_ZEROFunction object ('<=ZERO').
toString() - Method in class geneticWedge.gp.function.LESS_THAN_ZEROFunction
Returns a String representation of a LESS_THAN_ZEROFunction object ('toString() - Method in class geneticWedge.gp.function.LogFunction
Returns a String representation of a LogFunction object ('ln').
toString() - Method in class geneticWedge.gp.function.MaxFunction
Returns a String representation of a MaxFunction object ('MAX').
toString() - Method in class geneticWedge.gp.function.MinFunction
Returns a String representation of a MinFunction object ('MIN').
toString() - Method in class geneticWedge.gp.function.MultiplicationFunction
Returns a String representation of a MultiplicationFunction object ('×').
toString() - Method in class geneticWedge.gp.function.NANDFunction
Returns a String representation of a NANDFunction object ('NAND').
toString() - Method in class geneticWedge.gp.function.NOTFunction
Returns a String representation of a NOTFunction object ('NOT').
toString() - Method in class geneticWedge.gp.function.ORFunction
Returns a String representation of an ORFunction object ('OR').
toString() - Method in class geneticWedge.gp.function.PowerFunction
Returns a String representation of a PowerFunction object ('^').
toString() - Method in class geneticWedge.gp.function.SineFunction
Returns a String representation of a SineFunction object ('sin').
toString() - Method in class geneticWedge.gp.function.SqrtFunction
Returns a String representation of a SqrtFunction object ('sqrt').
toString() - Method in class geneticWedge.gp.function.SubtractionFunction
Returns a String representation of a SubtractionFunction object ('-').
toString() - Method in class geneticWedge.gp.function.TanFunction
Returns a String representation of a TanFunction object ('tan').
toString() - Method in class geneticWedge.gp.function.UnipolarSigmoidFunction
Returns a String representation of an UnipolarSigmoidFunction object ('uniSig').
toString() - Method in class geneticWedge.gp.function.XORFunction
Returns a String representation of an ORFunction object ('XOR').
toString() - Method in class geneticWedge.gp.Individual
Returns a string representation of this Individual.
toString() - Method in class geneticWedge.gp.Input
Returns a String representation of this object
toString() - Method in class geneticWedge.gp.StagnationStoppingCriterion
Returns a String representation of this StagnationStoppingCriterion.
toString() - Method in class geneticWedge.gp.StoppingCriterion
Returns a String represnetation of this StoppingCriterion.
toStringFunction() - Method in class geneticWedge.gp.Individual
Returns a string representation of this Individual in the format of a mathematical function.
tournamentSize - Variable in class geneticWedge.gp.AbstractPopulation
The size of the tournament used during tournament selection.
TreeFrame - Class in geneticWedge.gp.display
TreeFrame is a JFrame that holds a TreePanel and displays GP trees.
TreeFrame(Individual, String) - Constructor for class geneticWedge.gp.display.TreeFrame
Constuctor takes an Individual and a title String.
TreePanel - Class in geneticWedge.gp.display
TreePanel is a JPanel that draws GP trees onto itself.
TreePanel(Individual) - Constructor for class geneticWedge.gp.display.TreePanel
Constructor takes the Individual that it is to draw as an input
TwoInputFunction - Class in geneticWedge.gp.function
Abstract parent of all binary functions.
TwoInputFunction() - Constructor for class geneticWedge.gp.function.TwoInputFunction
The constructor sets the number of inputs required to 2
TwoInputFunction(int) - Constructor for class geneticWedge.gp.function.TwoInputFunction
This constructor allows the creation of Functions with assigned complexity values, rather than the default values.

U

UnipolarSigmoidFunction - Class in geneticWedge.gp.function
UnpolarSigmoidFunction is a unary function commonly used in Artificial Neural Networks.
UnipolarSigmoidFunction() - Constructor for class geneticWedge.gp.function.UnipolarSigmoidFunction
constructor
update(Individual) - Method in class geneticWedge.gp.display.TreeFrame
update replaces the displayed Individual with the new Individual ind.
update(Individual) - Method in class geneticWedge.gp.display.TreePanel
Changes the Individual to be drawn
UpdateFrame - Class in geneticWedge.gp.display
UpdateFrame updates a TreeFrame by replacing the displayed Individual with a new randomly generated Individual at 3-second intervals.
UpdateFrame(TreeFrame, Function[], Input[], Constant[]) - Constructor for class geneticWedge.gp.display.UpdateFrame
 
usesValidation() - Method in class geneticWedge.gp.EvaluativeStoppingCriterion
Early Stopping may be carried out based on changes in the training fitness or the validation fitness.
Utils - Class in geneticWedge.gp
Utils contains a number of static methods of use to various members of the gp package.
Utils() - Constructor for class geneticWedge.gp.Utils
 

V

valueOf(String) - Static method in enum geneticWedge.gp.AbstractPopulation.FitnessFunction
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum geneticWedge.gp.AbstractPopulation.SelectionMethod
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum geneticWedge.gp.dataAnalysis.DataAcquirer.ScalarData
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum geneticWedge.gp.dataAnalysis.DataAcquirer.VectorData
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum geneticWedge.gp.FitnessShare.FitnessShareFunction
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum geneticWedge.gp.FitnessShare.ShareType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum geneticWedge.gp.IndividualDescriptor.IndividualGrowMethod
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum geneticWedge.gp.io.XMLTreeHandler.IncludeData
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum geneticWedge.gp.Mutation.MutationOperator
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum geneticWedge.gp.Population.PerformanceFunction
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum geneticWedge.gp.PopulationDescriptor.PopulationGrowMethod
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum geneticWedge.gp.postProcess.PostProcessor.SELECT_MODE
Returns the enum constant of this type with the specified name.
values() - Static method in enum geneticWedge.gp.AbstractPopulation.FitnessFunction
Returns an array containing the constants of this enum type, in the order they're declared.
values() - Static method in enum geneticWedge.gp.AbstractPopulation.SelectionMethod
Returns an array containing the constants of this enum type, in the order they're declared.
values() - Static method in enum geneticWedge.gp.dataAnalysis.DataAcquirer.ScalarData
Returns an array containing the constants of this enum type, in the order they're declared.
values() - Static method in enum geneticWedge.gp.dataAnalysis.DataAcquirer.VectorData
Returns an array containing the constants of this enum type, in the order they're declared.
values() - Static method in enum geneticWedge.gp.FitnessShare.FitnessShareFunction
Returns an array containing the constants of this enum type, in the order they're declared.
values() - Static method in enum geneticWedge.gp.FitnessShare.ShareType
Returns an array containing the constants of this enum type, in the order they're declared.
values() - Static method in enum geneticWedge.gp.IndividualDescriptor.IndividualGrowMethod
Returns an array containing the constants of this enum type, in the order they're declared.
values() - Static method in enum geneticWedge.gp.io.XMLTreeHandler.IncludeData
Returns an array containing the constants of this enum type, in the order they're declared.
values() - Static method in enum geneticWedge.gp.Mutation.MutationOperator
Returns an array containing the constants of this enum type, in the order they're declared.
values() - Static method in enum geneticWedge.gp.Population.PerformanceFunction
Returns an array containing the constants of this enum type, in the order they're declared.
values() - Static method in enum geneticWedge.gp.PopulationDescriptor.PopulationGrowMethod
Returns an array containing the constants of this enum type, in the order they're declared.
values() - Static method in enum geneticWedge.gp.postProcess.PostProcessor.SELECT_MODE
Returns an array containing the constants of this enum type, in the order they're declared.

W

warning(SAXParseException) - Method in class geneticWedge.gp.io.XMLTreeHandler
Receive notification of a parser warning.
writeFile(String, NumericData, boolean, double, double) - Static method in class geneticWedge.gp.io.CSVWriter
Writes data from a NumericData object to a csv file.
writeFile(String, NumericData, boolean) - Static method in class geneticWedge.gp.io.CSVWriter
Writes data from a NumericData object to a csv file.
writeFile(String, String[], String[], double[][], boolean) - Static method in class geneticWedge.gp.io.CSVWriter
Writes data to a csv file.
writeFile(String, String[], String[], NumericData, boolean, double, double) - Static method in class geneticWedge.gp.io.CSVWriter
Writes data to a csv file, normalising it to the range [minNormalisedValue,maxNormalisedValue].
writeInputUseData(String) - Static method in class geneticWedge.gp.demo.DemoUtils
 
writeOutputs(String, String, Object[][], Object[][], Object[][]) - Method in class geneticWedge.gp.io.ResultWriter
This method writes the outputs resulting from training, validation and test data to file.
writeResults(String, Population, StoppingCriterion, boolean, int, double[][], double[], double[][], double[]) - Method in class geneticWedge.gp.io.ResultWriter
Writes results of evolution for the Population provided.
writeResults(String, Population, StoppingCriterion, boolean, int, double[][], double[], double[][], double[], double[][], double[]) - Method in class geneticWedge.gp.io.ResultWriter
Writes results of evolution for the Population provided.
writeSummaryInfo(String, String, double[]) - Method in class geneticWedge.gp.io.ResultWriter
This method writes an array of data to a file.
writeSummaryInfo(String, String, double[][]) - Method in class geneticWedge.gp.io.ResultWriter
This method writes a 2-D array of data to a file.
writeSummaryInfo(String, String, double[][][]) - Method in class geneticWedge.gp.io.ResultWriter
This method writes a 3-D array of data to a file.
writeXML(Individual, String) - Static method in class geneticWedge.gp.io.XMLWriter
This method writes the nodes within an Individual as an XML file.

X

XMLDataReader - Class in geneticWedge.gp.io
This class contains static methods for reading XML files and returning NumericData objects.
XMLDataReader() - Constructor for class geneticWedge.gp.io.XMLDataReader
 
XMLTreeHandler - Class in geneticWedge.gp.io
This class can read and extract data from XML files.
XMLTreeHandler(String, XMLTreeHandler.IncludeData) - Constructor for class geneticWedge.gp.io.XMLTreeHandler
Constructor
XMLTreeHandler.IncludeData - Enum in geneticWedge.gp.io
IncludeData determines which data will be retrieved from the XML file.
XMLWriter - Class in geneticWedge.gp.io
This class allows the writing of an Individual as an XML file.
XMLWriter() - Constructor for class geneticWedge.gp.io.XMLWriter
 
XORFunction - Class in geneticWedge.gp.function
XORFunction is the 'exclusive or' function.
XORFunction() - Constructor for class geneticWedge.gp.function.XORFunction
constructor

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