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

A

ABS_REF_PERIODS - Static variable in class netevo.features.Feature
 
AbsRefPeriods - Class in netevo.features
Feature for the evolution of SNN absolute refractory periods [ms].
AbsRefPeriods(Decoder) - Constructor for class netevo.features.AbsRefPeriods
Constructs the feature with default min = 0.0, max = 20.0.
addFeature(Feature) - Method in class netevo.Evolver
Adds a feature to the feature list.
addFunction(Function, Evolver) - Method in class netevo.features.Functions
Adds an activation function to the pool.

B

best - Variable in class netevo.misc.NetReporter
The overall best individual.
bestFitness - Variable in class netevo.misc.NetReporter
Fitness value of the overall best net.
bestRun - Variable in class netevo.misc.NetReporter
Run where overall best net emerged.
Bias - Class in netevo.features
Feature for the evolution of neuron biases.
Bias(Decoder) - Constructor for class netevo.features.Bias
Constructs the feature with min = -10.0, max = 10.0.
BIAS - Static variable in class netevo.features.Feature
 
BitDecoder - Class in netevo.decoders
Decoder for BitChromosomes.
BitDecoder() - Constructor for class netevo.decoders.BitDecoder
Constructs the BitDecoder with gene length = 8.
BP_TRAINING - Static variable in class netevo.features.Feature
 
BPTraining - Class in netevo.features
Feature to evolve BackProp training parameters.
BPTraining(Decoder) - Constructor for class netevo.features.BPTraining
Constructs the feature.
buildMatrix(NeuralNet) - Method in class netevo.NetEvolver
Builds a net matrix from an arbitrary network.
buildMatrix(NeuralNet) - Method in class netevo.SpikingNetEvolver
Builds a spike matrix from an arbitrary network.

C

calcFitness() - Method in class netevo.NetPhenotype
Calculates the fitness of this phenotype instance.
chromosome - Variable in class netevo.decoders.Decoder
The chromosome to decode.
chromosomeNumber - Variable in class netevo.decoders.Decoder
The chromosome index.
Classification - Class in netevo.fitness
Classification accuracy based on winner-takes-all evaluation of network output.
Classification(PatternSet) - Constructor for class netevo.fitness.Classification
Constructs the fitness function with a test set.
clearFunctionPool() - Method in class netevo.features.Functions
Removes all activation functions from the pool.
clone() - Method in class netevo.decoders.Decoder
Return a shallow clone.
clone() - Method in class netevo.misc.Matrix
A deep clone.
clone() - Method in class netevo.misc.NetMatrix
A deep clone.
clone() - Method in class netevo.misc.SpikeMatrix
A deep clone.
clone() - Method in class netevo.NetPhenotype
Returns a shallow clone.
cloneLink(Link, Neuron, Neuron, double) - Static method in class netevo.misc.Utilities
Clones a given link and connects it with the given parameters.
close() - Method in class netevo.misc.EvoGenStats
Close the stats file.
compareTo(Feature) - Method in class netevo.features.Feature
The natural ordering based on IDs is used for the order of decoding features.
compute(NeuralNet) - Method in class netevo.fitness.FitnessFunction
Computes the complete fitness with potential regularization.
createLinks(NeuralNet) - Method in class netevo.NetEvolver
Adds the links to the generated network.
createLinks(NeuralNet) - Method in class netevo.SpikingNetEvolver
Creates the spiking links with their spiking parameters.
createNet(NeuralNet) - Method in class netevo.NetEvolver
Creates a network based on the net matrix.
createNeurons(NeuralNet) - Method in class netevo.NetEvolver
Adds the neurons defined in matrix to net, which is built in createNet().
createNeurons(NeuralNet) - Method in class netevo.SpikingNetEvolver
Creates the spiking neurons with their spiking parameters.

D

Decoder - Class in netevo.decoders
Interpret a JEvolution Chromosome, calculate feature lengths, and read bits, integers and real numbers.
Decoder() - Constructor for class netevo.decoders.Decoder
Constructs the Decoder.
decoder - Variable in class netevo.features.Feature
The decoder for this Feature.
Delays - Class in netevo.features
Feature for the evolution of SNN link delays [ms].
Delays(Decoder) - Constructor for class netevo.features.Delays
Constructs the feature with default min = 0.0, max = 10.0.
DELAYS - Static variable in class netevo.features.Feature
 
develop(List<Chromosome>) - Method in class netevo.Evolver
Develops the given list of chromosomes into a neural network and training infrastructure depending on the features to be evolved.
develop() - Method in class netevo.features.AbsRefPeriods
Develops the feature.
develop() - Method in class netevo.features.Bias
Develops the feature.
develop() - Method in class netevo.features.BPTraining
Develops the feature fields.
develop() - Method in class netevo.features.Delays
Develops the feature.
develop() - Method in class netevo.features.Feature
Develops the feature.
develop() - Method in class netevo.features.Functions
Collects the functions from the pool and puts it into a list according to the neuron order.
develop() - Method in class netevo.features.IntValue
Develops the feature.
develop() - Method in class netevo.features.Links
Develops the feature.
develop() - Method in class netevo.features.Neurons
Develops the feature.
develop() - Method in class netevo.features.Patterns
Develops the feature.
develop() - Method in class netevo.features.RealValues
Develops the feature by decoding all real values.
develop() - Method in class netevo.features.RelRefPeriods
Develops the feature.
develop() - Method in class netevo.features.RpropTraining
Develops the feature fields.
develop() - Method in class netevo.features.Thresholds
Develops the feature.
develop() - Method in class netevo.features.Weights
Develops the feature.
develop() - Method in class netevo.NetEvolver
Creates the evolved net from the net matrix.
develop() - Method in class netevo.SpikingNetEvolver
Creates the evolved net from the net matrix.
develop(NeuralNet) - Method in class netevo.TrainEvolver
Trains the given network with the already developed infrastructure.
doInputs(boolean) - Method in class netevo.features.Functions
Sets status of input neuron AFs.
doOntogeny(List<Chromosome>) - Method in class netevo.NetPhenotype
Maps the genotype to a phenotype network.
doOutputs(boolean) - Method in class netevo.features.Functions
Sets status of output neuron AFs.
doStatistics(Population) - Method in class netevo.misc.NetReporter
Does population statistics, records the best individual of the run.
doStatistics() - Method in class netevo.misc.NetReporter
Does stats after end of run.

E

EPOCHS - Static variable in class netevo.features.BPTraining
The feature fields to be evolved.
EPOCHS - Static variable in class netevo.features.RpropTraining
The feature fields to be evolved.
ETA_MINUS - Static variable in class netevo.features.RpropTraining
 
ETA_PLUS - Static variable in class netevo.features.RpropTraining
 
EvoGenStats - Class in netevo.misc
Create per-generation evolution statistics, and write them to a CSV file.
EvoGenStats(String) - Constructor for class netevo.misc.EvoGenStats
Create and open a new stats file.
Evolver - Class in netevo
The master of evolution.
Evolver(NeuralNet, FitnessFunction) - Constructor for class netevo.Evolver
Creates the Evolver for network evolution only.
Evolver(NeuralNet, PatternSet, FitnessFunction) - Constructor for class netevo.Evolver
Creates the Evolver for network and training evolution.
Evolver(SpikingNeuralNet, FitnessFunction) - Constructor for class netevo.Evolver
Creates the evolver for a spiking neural network.
Evolver() - Constructor for class netevo.Evolver
 
evolver - Variable in class netevo.features.Feature
The evolution master.

F

Feature - Class in netevo.features
A Feature describes a specific aspect of the neural network, and contains the methods to develop it from the chromosome.
Feature(Decoder) - Constructor for class netevo.features.Feature
Constructs the feature with its decoder.
fill(double) - Method in class netevo.misc.Matrix
Sets all matrix elements to the same value.
FitnessFunction - Class in netevo.fitness
Abstract base class for fitness functions.
FitnessFunction() - Constructor for class netevo.fitness.FitnessFunction
 
FUNCTIONS - Static variable in class netevo.features.Feature
 
Functions - Class in netevo.features
Evolve activation functions for each neuron.
Functions(Decoder) - Constructor for class netevo.features.Functions
Constructs the feature.

G

geneLength - Variable in class netevo.decoders.Decoder
Length of the gene on the chromosome.
geneStart - Variable in class netevo.decoders.Decoder
The start index of a gene on the chromosome.
getAbsRefPeriod(int) - Method in class netevo.misc.SpikeMatrix
Returns an absolute refractory period value.
getBestIndividual() - Method in class netevo.misc.NetReporter
Returns the best individual of the current run so far.
getBias(int) - Method in class netevo.misc.NetMatrix
Returns a bias value.
getBiasCount() - Method in class netevo.misc.NetMatrix
Returns the number of biases encoded in the matrix.
getBiasCount() - Method in class netevo.NetEvolver
Returns the number of bias values to be evolved.
getChromosome() - Method in class netevo.decoders.Decoder
Returns the chromosome, for which the decoder is responsible.
getChromosomeNumber() - Method in class netevo.decoders.Decoder
Returns the chromosome number for this decoder.
getClassName(Object) - Static method in class netevo.misc.Utilities
Returns the unqualified class name, i.e., with all package names dropped.
getDecoder() - Method in class netevo.features.Feature
Return the decoder used by this feature.
getDigits(int, int) - Static method in class netevo.misc.Utilities
Calculate the minimal number of digits needed to represent the value in the given number base.
getField(int) - Method in class netevo.features.Feature
Returns a specific field of a sub-feature.
getFitness(NeuralNet) - Method in class netevo.fitness.Classification
Returns the classification accuracy in [0, 1] using Boone's NetError class for calculating the classification error.
getFitness(NeuralNet) - Method in class netevo.fitness.FitnessFunction
Computes a fitness of the given network.
getFitness(NeuralNet) - Method in class netevo.fitness.NetError
Returns the network fitness according to 1 / (1 + netError).
getFitness() - Method in class netevo.NetPhenotype
Returns the fitness of this phenotype instance.
getFitnessFunction() - Method in class netevo.Evolver
Returns the fitness function.
getFunctionCount() - Method in class netevo.features.Functions
Returns the number of activation functions in the pool.
getGeneLength() - Method in class netevo.decoders.Decoder
Returns the length (number of bases) of a gene on the chromosome.
getGeneStart() - Method in class netevo.decoders.Decoder
Returns the start index of the gene on the chromosome.
getHiddenCount() - Method in class netevo.NetEvolver
Returns the number of hidden neurons of the template.
getId() - Method in class netevo.features.Feature
Returns the unique feature ID, which is used to assign a feature to the corresponding evolver.
getInputCount() - Method in class netevo.NetEvolver
Returns the number of input neurons of the template.
getInputNeuronCount() - Method in class netevo.misc.NetMatrix
Returns the number of input neurons encoded with this matrix.
getLinkCount() - Method in class netevo.misc.NetMatrix
Returns the number of links encoded in the matrix.
getMaxValue() - Method in class netevo.features.Feature
Returns the maximal value to develop.
getMinValue() - Method in class netevo.features.Feature
Returns the minimal value to develop.
getNet() - Method in class netevo.NetEvolver
Returns the evolved network.
getNet() - Method in class netevo.NetPhenotype
Returns the network represented by this phenotype.
getNetEvolver() - Method in class netevo.Evolver
Returns the net evolver.
getNeuronCount() - Method in class netevo.misc.NetMatrix
Returns the number of neurons encoded with this matrix.
getNeuronCount() - Method in class netevo.NetEvolver
Returns the total number of neurons of the template.
getOutputCount() - Method in class netevo.NetEvolver
Returns the number of output neurons of the template.
getPatternCount() - Method in class netevo.TrainEvolver
Returns the number of patterns in the template set.
getPrune(int) - Method in class netevo.misc.NetMatrix
Returns the prune status.
getRegFactor() - Method in class netevo.fitness.FitnessFunction
Returns the regularization factor.
getRelRefPeriod(int) - Method in class netevo.misc.SpikeMatrix
Returns a relative refractory period value.
getThreshold(int) - Method in class netevo.misc.SpikeMatrix
Returns a threshold value.
getTopologicalSort(NeuralNet) - Static method in class netevo.misc.Utilities
Returns a sorted list of all neurons of a network in the order input-hidden-output.
getTrainer() - Method in class netevo.TrainEvolver
Returns the evolved trainer.
getTrainEvolver() - Method in class netevo.Evolver
Returns the train evolver.
getType(int) - Method in class netevo.misc.NetMatrix
Returns a neuron type.
getValue() - Method in class netevo.features.IntValue
 
getValue(NeuralNet) - Method in class netevo.fitness.RegularizationFactor
Returns the factor value for set type.
getValue(int, int) - Method in class netevo.misc.Matrix
Returns a matrix element.
getValueCount() - Method in class netevo.features.Feature
Returns the number of values for this feature.
getValues() - Method in class netevo.features.RealValues
Returns the evolved real values.
getWeight() - Method in class netevo.fitness.RegularizationFactor
Returns the weight of the factor.
getWeightCount() - Method in class netevo.NetEvolver
Returns the number of weights (=links) to be evolved.

H

hasLink(int, int) - Method in class netevo.NetEvolver
Checks, if a link between the given row and column in the net matrix is existent.
hasPredecessor(int) - Method in class netevo.misc.NetMatrix
Checks if a vertex has a directed edge leading to it.
hasSuccessor(int) - Method in class netevo.misc.NetMatrix
Checks if a vertex has a directed edge leaving from it.
HIDDEN - Static variable in class netevo.misc.NetMatrix
A hidden neuron.

I

id - Variable in class netevo.features.Feature
The unique feature ID.
INPUT - Static variable in class netevo.misc.NetMatrix
An input neuron.
IntDecoder - Class in netevo.decoders
Decoder for IntChromosomes.
IntDecoder() - Constructor for class netevo.decoders.IntDecoder
Constructs the IntDecoder with a gene length of one.
IntValue - Class in netevo.features
An arbitrary feature described by a single integer value.
IntValue(Decoder, double, double) - Constructor for class netevo.features.IntValue
 
invalidate(int, int) - Method in class netevo.misc.Matrix
Invalidates an element in the matrix.
isAccelerate() - Method in class netevo.fitness.Classification
Returns the acceleration status.
isInputs() - Method in class netevo.features.Functions
Returns status of input neuron AFs.
isInputs() - Method in class netevo.features.Neurons
Returns status of input neuron evolution.
isLimited() - Method in class netevo.decoders.RealDecoder
Returns the status of limiting real numbers.
isOutputs() - Method in class netevo.features.Functions
Returns status of output neuron AFs.
isOutputs() - Method in class netevo.features.Neurons
Returns status of output neuron evolution.
isPruneInput() - Method in class netevo.NetEvolver
Returns the status of input neuron pruning.
isPruneOutput() - Method in class netevo.NetEvolver
Returns the status of output neuron pruning.
isValid(double) - Method in class netevo.misc.Matrix
Checks if the value is valid.
isValid(int, int) - Method in class netevo.misc.Matrix
Checks if the element has a valid value.
isValid() - Method in class netevo.misc.NetMatrix
Checks if the net has at least one input and one output neuron.

L

LEARN_RATE - Static variable in class netevo.features.BPTraining
 
LEARN_RATE - Static variable in class netevo.features.RpropTraining
 
LINKS - Static variable in class netevo.features.Feature
 
Links - Class in netevo.features
Feature for the evolution of links.
Links(Decoder) - Constructor for class netevo.features.Links
Constructs the feature.

M

Matrix - Class in netevo.misc
A matrix.
Matrix(int, int) - Constructor for class netevo.misc.Matrix
Constructs an m x n matrix with all elements invalidated.
Matrix(int, int, double) - Constructor for class netevo.misc.Matrix
Constructs an m x n matrix with all elements set to 'value'.
matrix - Variable in class netevo.misc.Matrix
The matrix.
maxValue - Variable in class netevo.features.Feature
The maximal value to develop.
MIN_ERROR - Static variable in class netevo.features.BPTraining
 
MIN_ERROR - Static variable in class netevo.features.RpropTraining
 
minValue - Variable in class netevo.features.Feature
The minimal value to develop.
MOMENTUM - Static variable in class netevo.features.BPTraining
 

N

nameBase - Variable in class netevo.misc.NetReporter
File name base string, for saving winner networks.
net - Variable in class netevo.NetEvolver
The evolved net or the template net, if nothing to evolve.
NetError - Class in netevo.fitness
Standard Boone based fitness function returning output neuron errors on a test set.
NetError(PatternSet) - Constructor for class netevo.fitness.NetError
Constructs the fitness function with a test set.
netErrorString(NeuralNet, PatternSet) - Method in class netevo.misc.NetReporter
Prints some error measures for net and patterns.
netevo - package netevo
To start and get an overview, please, look at the Evolver base class.
netevo.decoders - package netevo.decoders
 
netevo.features - package netevo.features
 
netevo.fitness - package netevo.fitness
 
netevo.misc - package netevo.misc
 
NetEvoException - Exception in netevo.misc
General Netevo exception.
NetEvoException() - Constructor for exception netevo.misc.NetEvoException
 
NetEvoException(String) - Constructor for exception netevo.misc.NetEvoException
 
NetEvoException(Throwable) - Constructor for exception netevo.misc.NetEvoException
 
NetEvoException(String, Throwable) - Constructor for exception netevo.misc.NetEvoException
 
netEvolver - Variable in class netevo.Evolver
The net evolution master.
NetEvolver - Class in netevo
The base class for neural network evolution.
NetEvolver(NeuralNet) - Constructor for class netevo.NetEvolver
Creates the NetEvolver.
NetMatrix - Class in netevo.misc
A matrix containing all relevant network information.
NetMatrix(int) - Constructor for class netevo.misc.NetMatrix
Constructs an net matrix with three extra columns and all elements marked as unused.
NetPhenotype - Class in netevo
Phenotype implementation for the JEvolution package, using Boone neural networks.
NetPhenotype() - Constructor for class netevo.NetPhenotype
 
NetPhenotype(Evolver) - Constructor for class netevo.NetPhenotype
Create a new NetPhenotype for the evolution of Boone neural networks.
NetReporter - Class in netevo.misc
Accumulate and print evolution run statistics.
NetReporter(PrintWriter, String) - Constructor for class netevo.misc.NetReporter
Constructs the stat module.
NEURONS - Static variable in class netevo.features.Feature
 
Neurons - Class in netevo.features
Feature for the evolution of hidden neurons.
Neurons(Decoder) - Constructor for class netevo.features.Neurons
Constructs the feature.

O

OUTPUT - Static variable in class netevo.misc.NetMatrix
An output neuron.

P

params - Variable in class netevo.features.Feature
The field features (null, if not used).
PATTERNS - Static variable in class netevo.features.Feature
 
Patterns - Class in netevo.features
A feature for the evolution of training data.
Patterns(Decoder) - Constructor for class netevo.features.Patterns
Constructs the feature.
prepare() - Method in class netevo.Evolver
Prepares net evolution.
printOut - Variable in class netevo.misc.NetReporter
Output where to write the result messages.
pruneEdges(int) - Method in class netevo.misc.NetMatrix
Prunes all the edges from and to the given vertex.
pruneInput - Variable in class netevo.NetEvolver
Indicates pruning of ineffective input neurons.
pruneNeurons(boolean, boolean) - Method in class netevo.misc.NetMatrix
Prunes non-functional vertices.
pruneOutput - Variable in class netevo.NetEvolver
Indicates pruning of ineffective output neurons.

R

read(int, int, int) - Method in class netevo.decoders.Decoder
Reads the given number of integer values.
read(int, double, double) - Method in class netevo.decoders.Decoder
Reads the given number of double values.
read(int) - Method in class netevo.decoders.Decoder
Reads the given number of bits.
readBit(int) - Method in class netevo.decoders.BitDecoder
Returns the bit at the given index.
readBit(int) - Method in class netevo.decoders.Decoder
Read a bit from the given chromosome.
readBit(int) - Method in class netevo.decoders.IntDecoder
Decode a bit of the chromosome.
readBit(int) - Method in class netevo.decoders.RealDecoder
Returns a bit obeying the limited flag.
readInt(int, double, double) - Method in class netevo.decoders.BitDecoder
Returns the binary-encoded integer.
readInt(int, double, double) - Method in class netevo.decoders.Decoder
Read an integer from the chromosome.
readInt(int, double, double) - Method in class netevo.decoders.IntDecoder
Decodes an integer from the IntChromosome.
readInt(int, double, double) - Method in class netevo.decoders.RealDecoder
Returns the real-encoded integer obeying the limited flag.
readReal(int, double, double) - Method in class netevo.decoders.BitDecoder
Returns the binary-encoded double.
readReal(int, double, double) - Method in class netevo.decoders.Decoder
Read a real value from the chromosome.
readReal(int, double, double) - Method in class netevo.decoders.IntDecoder
Decodes a real from an IntChromosome by simply using readInt().
readReal(int, double, double) - Method in class netevo.decoders.RealDecoder
Returns the real-encoded double obeying the limited flag.
RealDecoder - Class in netevo.decoders
Decoder for RealChromosomes.
RealDecoder() - Constructor for class netevo.decoders.RealDecoder
Constructs the RealDecoder with a gene length of one and without limiting of real numbers.
RealValues - Class in netevo.features
An arbitrary feature described by a number of real values.
RealValues(Decoder) - Constructor for class netevo.features.RealValues
Constructs a single value in the unit interval.
RealValues(Decoder, int) - Constructor for class netevo.features.RealValues
Constructs a number of values in the unit interval.
RealValues(Decoder, double, double) - Constructor for class netevo.features.RealValues
Constructs a single value with min and max value.
RealValues(Decoder, int, double, double) - Constructor for class netevo.features.RealValues
Constructs the feature.
REG_HINTON - Static variable in class netevo.fitness.RegularizationFactor
 
REG_LINK - Static variable in class netevo.fitness.RegularizationFactor
 
REG_NEURON - Static variable in class netevo.fitness.RegularizationFactor
The supported types of regularization.
REG_RUMELHART - Static variable in class netevo.fitness.RegularizationFactor
 
RegularizationFactor - Class in netevo.fitness
Calculator of a regularization factor for network fitness.
RegularizationFactor(int) - Constructor for class netevo.fitness.RegularizationFactor
Constructs regularization of a given type.
REL_REF_PERIODS - Static variable in class netevo.features.Feature
 
RelRefPeriods - Class in netevo.features
Feature for the evolution of SNN relative refractory periods [ms].
RelRefPeriods(Decoder) - Constructor for class netevo.features.RelRefPeriods
Constructs the feature with default min = 0.0, max = 5.0.
reportEnd() - Method in class netevo.misc.NetReporter
Print global stats after end of evolution.
RPROP_TRAINING - Static variable in class netevo.features.Feature
 
RpropTraining - Class in netevo.features
Feature to evolve RProp training parameters.
RpropTraining(Decoder) - Constructor for class netevo.features.RpropTraining
Constructs the feature.
runCount - Variable in class netevo.misc.NetReporter
The number of completed runs.

S

setAbsRefPeriod(int, double) - Method in class netevo.misc.SpikeMatrix
Sets the absolute refractory period in the corresponding column.
setAbsRefPeriods(List<Double>) - Method in class netevo.SpikingNetEvolver
Sets the neurons' absolute refractory periods in the spike matrix.
setAccelerate(boolean) - Method in class netevo.fitness.Classification
Sets the acceleration status.
setBias(int, double) - Method in class netevo.misc.NetMatrix
Sets a value in the bias column.
setBias(List<Double>) - Method in class netevo.NetEvolver
Sets evolved weights in the net matrix.
setChromosome(Chromosome) - Method in class netevo.decoders.Decoder
Sets the chromosome to be decoded.
setChromosome(List<Chromosome>) - Method in class netevo.decoders.Decoder
Sets the chromosome to be decoded from a list of chromosomes.
setChromosomeNumber(int) - Method in class netevo.decoders.Decoder
Sets the chromosome number for this decoder.
setDecoder(Decoder) - Method in class netevo.features.Feature
Sets the decoder used by this feature.
setDelays(List<Double>) - Method in class netevo.SpikingNetEvolver
Stores the evolved link delays in the spike matrix.
setFunctions(List<Function>, boolean, boolean) - Method in class netevo.NetEvolver
Puts the evolved functions on the template neurons in 'topSort', from where they are later cloned, when the network is constructed.
setGeneLength(int) - Method in class netevo.decoders.Decoder
Sets the length (number of bases) of a gene on the chromosome.
setGeneLength(int) - Method in class netevo.decoders.IntDecoder
Always keeps length at 1.
setGeneLength(int) - Method in class netevo.decoders.RealDecoder
Always keeps length at 1.
setGeneStart(int) - Method in class netevo.decoders.Decoder
Sets the start index of the gene on the chromosome.
setInputs(boolean) - Method in class netevo.features.Neurons
Sets status of input neuron evolution.
setLimited(boolean) - Method in class netevo.decoders.RealDecoder
Sets the limiting of real numbers.
setLinks(List<Boolean>) - Method in class netevo.NetEvolver
Prunes evolved links in the net matrix.
setMaxValue(double) - Method in class netevo.features.Feature
Sets the maximal value to develop.
setMinValue(double) - Method in class netevo.features.Feature
Sets the minimal value to develop.
setNeurons(List<Boolean>) - Method in class netevo.NetEvolver
Prunes evolved neurons in the net matrix.
setOutputs(boolean) - Method in class netevo.features.Neurons
Sets status of output neuron evolution.
setPatterns(List<Boolean>) - Method in class netevo.TrainEvolver
Constructs the training set as a subset of the template set.
setPrune(int, boolean) - Method in class netevo.misc.NetMatrix
Sets the prune status.
setPruneInput(boolean) - Method in class netevo.NetEvolver
Sets the status of input neuron pruning.
setPruneOutput(boolean) - Method in class netevo.NetEvolver
Sets the status of output neuron pruning.
setRegFactor(RegularizationFactor) - Method in class netevo.fitness.FitnessFunction
Sets the regularization factor.
setRelRefPeriod(int, double) - Method in class netevo.misc.SpikeMatrix
Sets the relative refractory period in the corresponding column.
setRelRefPeriods(List<Double>) - Method in class netevo.SpikingNetEvolver
Sets the neurons' relative refractory periods in the spike matrix.
setThreshold(int, double) - Method in class netevo.misc.SpikeMatrix
Sets a value in the threshold column.
setThresholds(List<Double>) - Method in class netevo.SpikingNetEvolver
Stores the evolved threshold values in the spike matrix.
setTrainer(Trainer) - Method in class netevo.TrainEvolver
Sets the trainer to be evolved.
setType(int, int) - Method in class netevo.misc.NetMatrix
Sets a neuron type in the type column.
setup(Evolver) - Method in class netevo.features.AbsRefPeriods
Sets up the feature and its decoder.
setup(Evolver) - Method in class netevo.features.Bias
Sets up the feature and its decoder.
setup(Evolver) - Method in class netevo.features.BPTraining
Sets up the feature parameters.
setup(Evolver) - Method in class netevo.features.Delays
Sets up the feature and its decoder.
setup(Evolver) - Method in class netevo.features.Feature
Sets up the feature parameters.
setup(Evolver) - Method in class netevo.features.Functions
Sets up the feature by counting the number of neurons, for which functions should be evolved.
setup(Evolver) - Method in class netevo.features.IntValue
Sets up the feature parameters.
setup(Evolver) - Method in class netevo.features.Links
Sets up the feature and its decoder.
setup(Evolver) - Method in class netevo.features.Neurons
Sets up the feature by counting the number of neurons to be evolved.
setup(Evolver) - Method in class netevo.features.Patterns
Sets up the feature by counting the total number of patterns, from which a subset shall be evolved.
setup(Evolver) - Method in class netevo.features.RealValues
Sets up the feature parameters.
setup(Evolver) - Method in class netevo.features.RelRefPeriods
Sets up the feature and its decoder.
setup(Evolver) - Method in class netevo.features.RpropTraining
Sets up the feature parameters.
setup(Evolver) - Method in class netevo.features.Thresholds
Sets up the feature and its decoder.
setup(Evolver) - Method in class netevo.features.Weights
Sets up the feature and its decoder.
setupFields() - Method in class netevo.features.Feature
Sets up the fields with correct values.
setValue(int, int, double) - Method in class netevo.misc.Matrix
Sets a matrix elements to the given value.
setWeight(double) - Method in class netevo.fitness.RegularizationFactor
Sets the weight of the factor.
setWeights(List<Double>) - Method in class netevo.NetEvolver
Sets evolved weights in the net matrix.
SpikeMatrix - Class in netevo.misc
A matrix containing all relevant spiking network information.
SpikeMatrix(int) - Constructor for class netevo.misc.SpikeMatrix
Constructs an net matrix with three extra columns and all elements marked as unused.
SpikingNetEvolver - Class in netevo
The base class for the evolution of spiking neural networks evolution.
SpikingNetEvolver(SpikingNeuralNet) - Constructor for class netevo.SpikingNetEvolver
Creates the spiking net evolver.
SPLINE - Static variable in class netevo.features.Feature
 
stats - Variable in class netevo.misc.EvoGenStats
Stats array: mean/min/max/stdDev for fitness, links, units, cycles.
statsOut - Variable in class netevo.misc.EvoGenStats
Stats writer.

T

THRESHOLDS - Static variable in class netevo.features.Feature
 
Thresholds - Class in netevo.features
Feature for the evolution of SNN firing thresholds [mV].
Thresholds(Decoder) - Constructor for class netevo.features.Thresholds
Constructs the feature with default min = 0.0, max = 100.0.
toString() - Method in class netevo.decoders.Decoder
Returns a description of this Feature.
toString() - Method in class netevo.Evolver
Build a string describing the evolution setup and the chromosome structure.
toString() - Method in class netevo.features.BPTraining
Returns a string representation of the feature's BP training parameters.
toString() - Method in class netevo.features.Feature
Returns a description of this Feature.
toString() - Method in class netevo.features.RpropTraining
Returns a string representation of the feature's BP training parameters.
toString() - Method in class netevo.misc.Matrix
Returns the matrix in a basic rows/columns string format.
toString() - Method in class netevo.NetPhenotype
Returns a string representation of the network.
toXml(Element) - Method in class netevo.NetPhenotype
 
trainEvolver - Variable in class netevo.Evolver
The training infrastructure evolution master.
TrainEvolver - Class in netevo
Base class for training infrastructure evolution.
TrainEvolver(NeuralNet, PatternSet) - Constructor for class netevo.TrainEvolver
Constructs the training evolver with a trainer and a pattern set.
transferList - Variable in class netevo.decoders.Decoder
A utility list for data transfer.

U

Utilities - Class in netevo.misc
 
Utilities() - Constructor for class netevo.misc.Utilities
 

V

valueCount - Variable in class netevo.features.Feature
The number of values to develop.

W

WEIGHTS - Static variable in class netevo.features.Feature
The feature IDs also defining the order of feature construction.
Weights - Class in netevo.features
Feature for the evolution of link weights.
Weights(Decoder) - Constructor for class netevo.features.Weights
Constructs the feature with default min = -10.0, max = 10.0.
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