getCSCrossoverP ( self )

Return the probability of a context sensitive crossover operation occuring each turn during breeding

This should be a number from 0 to 1. The sum of all the genetic operation probability parameters must be exactly 1.

getCrossoverP ( self )

Return the probability of a standard crossover operation occuring each turn during breeding

This should be a number from 0 to 1. The sum of all the genetic operation probability parameters must be exactly 1.

getFitnessEvaluator ( self )

Return the fitness evaluator

This is an instance of FitnessEvaluator which is used to evaluate Program fitness.

getForceBest ( self )

Returns the number of instance of the best program per generation that will be forced to replicate

If its zero, the feature is effectively disabled

getInitialProgramDepth ( self )

Return the initial program depth

This is maximum initial program depth a Population will have.

getInput ( self )

Get the input list

The input list is a list of vectors represented as lists. There is no limit to the dimensionality of the vectors.

getMaxProgramDepth ( self )

Return the maximum program depth allowed

This is maximum program depth a Population can develop.

getMutateP ( self )

Return the probability of a mutation operation occuring each turn during breeding

This should be a number from 0 to 1. The sum of all the genetic operation probability parameters must be exactly 1.

getName ( self )

Return the name of this run

This can be used to log, save, load, and resume runs.

getOutput ( self )

Get the output list

The output list is a list of single outputs.

getPopulationSize ( self )

Return the population size

This is the size the population is initialize to and will remain throughout a run.

getPrecision ( self )

Returns the numeric value of how close a Program answer must be to be considered a hit

getProgramSelector ( self )

Return the program selector

This is an instance of ProgramSelector which is used to select programs from the Population.

getReplicateP ( self )

Return the probability of a replication operation occuring each turn during breeding

This should be a number from 0 to 1. The sum of all the genetic operation probability parameters must be exactly 1.

getVocabulary ( self )

Returns the vocabulary

The vocabulary is represented as a list containing three sublists in the following format: [ terminals-list, one-argument-function-list, two-argument-function-list ]

initialize ( self,  interpreter )

Initialize any remaining properties.

This should be called after command-line parameter application

inputCount ( self )

Returns the number of inputs in the input list

...

setCSCrossoverP ( self,  P )

Set the probability of a context sensitive crossover operation occuring each turn during breeding

This should be a number from 0 to 1. The sum of all the genetic operation probability parameters must be exactly 1.

setCrossoverP ( self,  P )

Set the probability of a standard crossover operation occuring each turn during breeding

This should be a number from 0 to 1. The sum of all the genetic operation probability parameters must be exactly 1.

setForceBest ( self,  forcebest )

Set the number of instance of the best program per generation that will be forced to replicate

If its zero, the feature is effectively disabled

setInitialProgramDepth ( self,  d )

Set the initial program depth

This is maximum initial program depth a Population will have.

setInput ( self,  input )

Set the input list

The input list is a list of vectors represented as lists. There is no limit to the dimensionality of the vectors.

setMaxProgramDepth ( self,  d )

Set the maximum program depth to allow

This is maximum program depth a Population can develop.

setMutateP ( self,  P )

Set the probability of a mutation operation occuring each turn during breeding

This should be a number from 0 to 1. The sum of all the genetic operation probability parameters must be exactly 1.

setName ( self,  name )

Set the name of this run

This can be used to log, save, load, and resume runs.

setOutput ( self,  output )

Set the output list

The output list is a list of single outputs.

setPopulationSize ( self,  s )

Set the size of the population to use

This is the size the population is initialize to and will remain throughout a run.

setPrecision ( self,  precision )

Sets the numeric value of how close a Program answer must be to be considered a hit

setReplicateP ( self,  P )

Set the probability of a replication operation occuring each turn during breeding

This should be a number from 0 to 1. The sum of all the genetic operation probability parameters must be exactly 1.

setVocabulary ( self,  vocabulary )

Set the vocabulary

The vocabulary is represented as a list containing three sublists in the following format: [ terminals-list, one-argument-function-list, two-argument-function-list ]

useFitnessProportionateSelection ( self,  fitnessDependence )

Use a fitness proportionate selection method

Program selection for genetic operations will be biased towards more fit individuals.

useInputsFromFile ( self,  inputsfile )

Use the input set contained in the specified file

The file must be in ASCII comma delimited (CSV) format. One input vector per line, with each dimension seperated by commas.

useLispExpressionOutputGeneration ( self,  expr )

Use the specified lisp expression to generate outputs

The specified expression should be a valid lisp expression accessible to the interpreter. The expression must expect the input vector values as lisp variables in the form INPUT1,INPUT2,...INPUTn for an n dimensional input space.

useLispFunctionDevianceCalculation ( self,  name )

Use the specified lisp function for deviance calculation

Sets the deviance calculation method to be based on a lisp function call with the specified name.

useOutputDevianceCalculation ( self )

Use the output list for deviance calculation

The output list is compared directly with the actual results of the Program being tested.

useOutputsFromFile ( self,  outputsfile )

Use the output set contained in the specified file

The file must be an ASCII file with one line per output. The can only be one output per line.

usePythonClassDevianceCalculation (
        self,
        module,
        classname,
        )

Use the specified DevianceCalculator subclass for deviance calculation

The name of a DevianceCalculator subclass must be specified along with the name of the module that contains it.

usePythonClassOutputGeneration (
        self,
        module,
        classname,
        )

Use the specied OutputGenerator subclass to generate outputs

The name of a OutputGenerator subclass must be specified along with the name of the module that contains it. When activated, this class should generate the output list based on the values in the input list.

useTournamentSelection ( self,  size )

Use a tourament selection method

Program selection for genetic operations will be based on the winner of a tournament of the specified size.

useVocabularyFile ( self,  filename )

Set the vocabulary to the contents of the specified file

The file must be an ASCII file with three lines. The first line should be a comma seperated list of TERMINAL values. The second line should be a comma seperated list of ONE-ARGUMENT lisp functions. The third line should be a comma seperated list of TWO-ARGUMENT functions.