currently I am working on a Jenetics (link to jenetics) implementation to optimize a particle accelerator beam line. My fitness function calls accelerator detector devices and is defined as follows:
private double fitness(final DoubleChromosome chromosomes) {
// private double fitness(final Genotype<DoubleGene> chromosomes) {
// Convert genes to a format the device scanner can understand
// we will inject a 1:n Set<List<Double>>
final Set<List<Double>> trimValues = new HashSet<>();
final List<Double> valueList = new ArrayList<>();
for (final DoubleGene chromosome : chromosomes) {
valueList.add(Double.valueOf(chromosome.doubleValue()));
}
trimValues.add(valueList);
....
more code specific to application
}
Jenetics' stream engine is initialized in a specific method:
public void initAlgorithm(final Object scanParameters) throws Exception {
if (scanParameters != null) {
/// See constructor of EvolvingImagesWorker
_geneticScanParameters = (GeneticScanParameters) scanParameters;
}
if (_geneticScanParameters.getTrimParameterSets() != null) {
final int chromosomeCount = _geneticScanParameters.getTrimParameterSets().size();
if (chromosomeCount > 0) {
ISeq<DoubleChromosome> chromosomeSet = ISeq.empty();
// create an ISeq of genes
for (final TrimParameterValueSet valueSet : _geneticScanParameters.getTrimParameterSets()) {
final double minValue = valueSet.getMinValue();
final double maxValue = valueSet.getMaxValue();
final double initialValue = (maxValue + minValue) / 2;
final DoubleGene doubleGene = DoubleGene.of(initialValue, minValue, maxValue);
final DoubleChromosome doubleChromosome = DoubleChromosome.of(doubleGene.newInstance());
chromosomeSet = chromosomeSet.append(doubleChromosome.newInstance());
}
Codec<DoubleChromosome, DoubleGene> codec = null;
try {
final Genotype<DoubleGene> genotype = Genotype.of(chromosomeSet);
codec = Codec.of(genotype.newInstance(), //
gt -> (DoubleChromosome) gt.getChromosome());
} catch (final IllegalArgumentException ex) {
MessageLogger.logError(getClass(), Thread.currentThread(), ex);
throw ex;
}
_scannerEngine = Engine.builder(this::fitness, codec) //
.executor(Executors.newSingleThreadExecutor()) // without this command, engine will be executed
// in
// parallel threads
.populationSize(_geneticScanParameters.getPopulationSize()) //
.optimize(_geneticScanParameters.getOptimizationStrategy()) //
.offspringFraction(_geneticScanParameters.getOffspringSize()) //
.survivorsSelector(new RouletteWheelSelector<>()) //
.offspringSelector(new TournamentSelector<>(_geneticScanParameters.getTournamentSizeLimit())) //
.alterers( //
new Mutator<>(_geneticScanParameters.getMutator()), //
new MeanAlterer<>(_geneticScanParameters.getMeanAlterer()) //
) //
.build();
} else {
throw new IllegalStateException(ERROR_INITSCANNER_NO_SETTING_DEVICE);
}
}
}
where:
private Engine<DoubleGene, Double> _scannerEngine = null;
What I would like to do is to call the fitness function such that I have the Genotype available in the fitness function to have access to the genes' values (settings I send to the accelerator). I already tried to define fitness() as follows:
private double fitness(final Genotype<DoubleChromosome> genotype) {
...
}
but this call causes a compliation error.
I had a look at your code and I think you want to do something like this:
class Foo {
// Your parameter class.
class TrimParameterSet {
double min, max;
}
static double fitness(final double[] values) {
// Your fitness function.
return 0;
}
public static void main(final String[] args) {
final List<TrimParameterSet> valueSets = ...;
final DoubleRange[] ranges = valueSets.stream()
.map(p -> DoubleRange.of(p.min, p.max))
.toArray(DoubleRange[]::new);
final Codec<double[], DoubleGene> codec = Codecs.ofVector(ranges);
final Engine<DoubleGene, Double> engine = Engine.builder(Foo::fitness, codec)
.build();
// ...
}
}
The double[]
array of your fitness function has a different range, accoriding to the defined ranges in your TrimParameterSet
class. If you want to define a direct fitness function, you have to define a genotype with a gene as parameter type.
double fitness(Genotype<DoubleGene> gt) {...}