private void saveSpecies(final EncogWriteHelper out, final Species species) {
out.addColumn("s");
out.addColumn(species.getAge());
out.addColumn(species.getBestScore());
out.addColumn(species.getGensNoImprovement());
out.writeLine();
for (final Genome genome : species.getMembers()) {
final NEATGenome neatGenome = (NEATGenome) genome;
out.addColumn("g");
out.addColumn(neatGenome.getAdjustedScore());
out.addColumn(neatGenome.getScore());
out.addColumn(neatGenome.getBirthGeneration());
out.writeLine();
for (final NEATNeuronGene neatNeuronGene : neatGenome.getNeuronsChromosome()) {
out.addColumn("n");
out.addColumn(neatNeuronGene.getId());
out.addColumn(neatNeuronGene.getActivationFunction());
out.addColumn(PersistNEATPopulation.neuronTypeToString(neatNeuronGene.getNeuronType()));
out.addColumn(neatNeuronGene.getInnovationId());
out.writeLine();
}
for (final NEATLinkGene neatLinkGene : neatGenome.getLinksChromosome()) {
out.addColumn("l");
out.addColumn(neatLinkGene.getId());
out.addColumn(neatLinkGene.isEnabled());
out.addColumn(neatLinkGene.getFromNeuronID());
out.addColumn(neatLinkGene.getToNeuronID());
out.addColumn(neatLinkGene.getWeight());
out.addColumn(neatLinkGene.getInnovationId());
out.writeLine();
}
}
}
/**
* Save segregate info.
*
* @param out The output file.
*/
private void saveSegregate(final EncogWriteHelper out) {
saveSubSection(out, "SEGREGATE", "CONFIG");
out.addSubSection("FILES");
out.addColumn("file");
out.addColumn("percent");
out.writeLine();
for (final AnalystSegregateTarget target : this.script.getSegregate().getSegregateTargets()) {
out.addColumn(target.getFile());
out.addColumn(target.getPercent());
out.writeLine();
}
}
/**
* Save the normalization data.
*
* @param out The output file.
*/
private void saveNormalize(final EncogWriteHelper out) {
saveSubSection(out, "NORMALIZE", "CONFIG");
out.addSubSection("RANGE");
out.addColumn("name");
out.addColumn("io");
out.addColumn("timeSlice");
out.addColumn("action");
out.addColumn("high");
out.addColumn("low");
out.writeLine();
for (final AnalystField field : this.script.getNormalize().getNormalizedFields()) {
out.addColumn(field.getName());
if (field.isInput()) {
out.addColumn("input");
} else {
out.addColumn("output");
}
out.addColumn(field.getTimeSlice());
switch (field.getAction()) {
case Ignore:
out.addColumn("ignore");
break;
case Normalize:
out.addColumn("range");
break;
case PassThrough:
out.addColumn("pass");
break;
case OneOf:
out.addColumn("oneof");
break;
case Equilateral:
out.addColumn("equilateral");
break;
case SingleField:
out.addColumn("single");
break;
default:
throw new AnalystError("Unknown action: " + field.getAction());
}
out.addColumn(field.getNormalizedHigh());
out.addColumn(field.getNormalizedLow());
out.writeLine();
}
}
/**
* Save the data fields.
*
* @param out The output file.
*/
private void saveData(final EncogWriteHelper out) {
saveSubSection(out, "DATA", "CONFIG");
out.addSubSection("STATS");
out.addColumn("name");
out.addColumn("isclass");
out.addColumn("iscomplete");
out.addColumn("isint");
out.addColumn("isreal");
out.addColumn("amax");
out.addColumn("amin");
out.addColumn("mean");
out.addColumn("sdev");
out.writeLine();
for (final DataField field : this.script.getFields()) {
out.addColumn(field.getName());
out.addColumn(field.isClass());
out.addColumn(field.isComplete());
out.addColumn(field.isInteger());
out.addColumn(field.isReal());
out.addColumn(field.getMax());
out.addColumn(field.getMin());
out.addColumn(field.getMean());
out.addColumn(field.getStandardDeviation());
out.writeLine();
}
out.flush();
out.addSubSection("CLASSES");
out.addColumn("field");
out.addColumn("code");
out.addColumn("name");
out.writeLine();
for (final DataField field : this.script.getFields()) {
if (field.isClass()) {
for (final AnalystClassItem col : field.getClassMembers()) {
out.addColumn(field.getName());
out.addColumn(col.getCode());
out.addColumn(col.getName());
out.addColumn(col.getCount());
out.writeLine();
}
}
}
}
/** {@inheritDoc} */
@Override
public void save(final OutputStream os, final Object obj) {
final EncogWriteHelper out = new EncogWriteHelper(os);
final RBFNetwork net = (RBFNetwork) obj;
final FlatNetworkRBF flat = (FlatNetworkRBF) net.getFlat();
out.addSection("RBF-NETWORK");
out.addSubSection("PARAMS");
out.addProperties(net.getProperties());
out.addSubSection("NETWORK");
out.writeProperty(BasicNetwork.TAG_BEGIN_TRAINING, flat.getBeginTraining());
out.writeProperty(BasicNetwork.TAG_CONNECTION_LIMIT, flat.getConnectionLimit());
out.writeProperty(BasicNetwork.TAG_CONTEXT_TARGET_OFFSET, flat.getContextTargetOffset());
out.writeProperty(BasicNetwork.TAG_CONTEXT_TARGET_SIZE, flat.getContextTargetSize());
out.writeProperty(BasicNetwork.TAG_END_TRAINING, flat.getEndTraining());
out.writeProperty(BasicNetwork.TAG_HAS_CONTEXT, flat.getHasContext());
out.writeProperty(PersistConst.INPUT_COUNT, flat.getInputCount());
out.writeProperty(BasicNetwork.TAG_LAYER_COUNTS, flat.getLayerCounts());
out.writeProperty(BasicNetwork.TAG_LAYER_FEED_COUNTS, flat.getLayerFeedCounts());
out.writeProperty(BasicNetwork.TAG_LAYER_CONTEXT_COUNT, flat.getLayerContextCount());
out.writeProperty(BasicNetwork.TAG_LAYER_INDEX, flat.getLayerIndex());
out.writeProperty(PersistConst.OUTPUT, flat.getLayerOutput());
out.writeProperty(PersistConst.OUTPUT_COUNT, flat.getOutputCount());
out.writeProperty(BasicNetwork.TAG_WEIGHT_INDEX, flat.getWeightIndex());
out.writeProperty(PersistConst.WEIGHTS, flat.getWeights());
out.writeProperty(BasicNetwork.TAG_BIAS_ACTIVATION, flat.getBiasActivation());
out.addSubSection("ACTIVATION");
for (final ActivationFunction af : flat.getActivationFunctions()) {
out.addColumn(af.getClass().getSimpleName());
for (int i = 0; i < af.getParams().length; i++) {
out.addColumn(af.getParams()[i]);
}
out.writeLine();
}
out.addSubSection("RBF");
for (final RadialBasisFunction rbf : flat.getRBF()) {
out.addColumn(rbf.getClass().getSimpleName());
out.addColumn(rbf.getWidth());
out.addColumn(rbf.getPeak());
for (int i = 0; i < rbf.getCenters().length; i++) {
out.addColumn(rbf.getCenters()[i]);
}
out.writeLine();
}
out.flush();
}
@Override
public void save(final OutputStream os, final Object obj) {
final EncogWriteHelper out = new EncogWriteHelper(os);
final NEATPopulation pop = (NEATPopulation) obj;
out.addSection("NEAT-POPULATION");
out.addSubSection("CONFIG");
out.writeProperty(PersistConst.ACTIVATION_CYCLES, pop.getActivationCycles());
if (pop.isHyperNEAT()) {
out.writeProperty(NEATPopulation.PROPERTY_NEAT_ACTIVATION, PersistNEATPopulation.TYPE_CPPN);
} else {
final ActivationFunction af = pop.getActivationFunctions().getList().get(0).getObj();
out.writeProperty(NEATPopulation.PROPERTY_NEAT_ACTIVATION, af);
}
out.writeProperty(PersistConst.INPUT_COUNT, pop.getInputCount());
out.writeProperty(PersistConst.OUTPUT_COUNT, pop.getOutputCount());
out.writeProperty(NEATPopulation.PROPERTY_CYCLES, pop.getActivationCycles());
out.writeProperty(NEATPopulation.PROPERTY_POPULATION_SIZE, pop.getPopulationSize());
out.writeProperty(NEATPopulation.PROPERTY_SURVIVAL_RATE, pop.getSurvivalRate());
out.addSubSection("INNOVATIONS");
if (pop.getInnovations() != null) {
for (final String key : pop.getInnovations().getInnovations().keySet()) {
final NEATInnovation innovation = pop.getInnovations().getInnovations().get(key);
out.addColumn(key);
out.addColumn(innovation.getInnovationID());
out.addColumn(innovation.getNeuronID());
out.writeLine();
}
}
out.addSubSection("SPECIES");
// make sure the best species goes first
final Species bestSpecies = pop.determineBestSpecies();
if (bestSpecies != null) {
saveSpecies(out, bestSpecies);
}
// now write the other species, other than the best one
for (final Species species : pop.getSpecies()) {
if (species != bestSpecies) {
saveSpecies(out, species);
}
}
out.flush();
}
/** {@inheritDoc} */
@Override
public void save(final OutputStream os, final Object obj) {
final EncogWriteHelper out = new EncogWriteHelper(os);
final BasicNetwork net = (BasicNetwork) obj;
final FlatNetwork flat = net.getStructure().getFlat();
out.addSection("BASIC");
out.addSubSection("PARAMS");
out.addProperties(net.getProperties());
out.addSubSection("NETWORK");
out.writeProperty(BasicNetwork.TAG_BEGIN_TRAINING, flat.getBeginTraining());
out.writeProperty(BasicNetwork.TAG_CONNECTION_LIMIT, flat.getConnectionLimit());
out.writeProperty(BasicNetwork.TAG_CONTEXT_TARGET_OFFSET, flat.getContextTargetOffset());
out.writeProperty(BasicNetwork.TAG_CONTEXT_TARGET_SIZE, flat.getContextTargetSize());
out.writeProperty(BasicNetwork.TAG_END_TRAINING, flat.getEndTraining());
out.writeProperty(BasicNetwork.TAG_HAS_CONTEXT, flat.getHasContext());
out.writeProperty(PersistConst.INPUT_COUNT, flat.getInputCount());
out.writeProperty(BasicNetwork.TAG_LAYER_COUNTS, flat.getLayerCounts());
out.writeProperty(BasicNetwork.TAG_LAYER_FEED_COUNTS, flat.getLayerFeedCounts());
out.writeProperty(BasicNetwork.TAG_LAYER_CONTEXT_COUNT, flat.getLayerContextCount());
out.writeProperty(BasicNetwork.TAG_LAYER_INDEX, flat.getLayerIndex());
out.writeProperty(PersistConst.OUTPUT, flat.getLayerOutput());
out.writeProperty(PersistConst.OUTPUT_COUNT, flat.getOutputCount());
out.writeProperty(BasicNetwork.TAG_WEIGHT_INDEX, flat.getWeightIndex());
out.writeProperty(PersistConst.WEIGHTS, flat.getWeights());
out.writeProperty(BasicNetwork.TAG_BIAS_ACTIVATION, flat.getBiasActivation());
out.addSubSection("ACTIVATION");
for (final ActivationFunction af : flat.getActivationFunctions()) {
String sn = af.getClass().getSimpleName();
// if this is an Encog class then only add the simple name, so it works with C#
if (sn.startsWith("org.encog.")) {
out.addColumn(sn);
} else {
out.addColumn(af.getClass().getName());
}
for (int i = 0; i < af.getParams().length; i++) {
out.addColumn(af.getParams()[i]);
}
out.writeLine();
}
out.flush();
}