/**
* Save the tasks.
*
* @param out The output file.
*/
private void saveTasks(final EncogWriteHelper out) {
out.addSection("TASKS");
final List<String> list = new ArrayList<String>();
list.addAll(this.script.getTasks().keySet());
Collections.sort(list);
for (final String key : list) {
final AnalystTask task = this.script.getTask(key);
out.addSubSection(task.getName());
for (final String line : task.getLines()) {
out.addLine(line);
}
}
}
/**
* Save the config info.
*
* @param out THe output file.
*/
private void saveConfig(final EncogWriteHelper out) {
saveSubSection(out, "SETUP", "CONFIG");
out.addSubSection("FILENAMES");
final List<String> list = this.script.getProperties().getFilenames();
for (final String key : list) {
final String value = this.script.getProperties().getFilename(key);
final File f = new File(value);
if ((f.getParent() != null) && f.getParent().equalsIgnoreCase(this.script.getBasePath())) {
out.writeProperty(key, f.getName());
} else {
out.writeProperty(key, value);
}
}
}
/** {@inheritDoc} */
@Override
public final void save(final OutputStream os, final Object obj) {
final EncogWriteHelper out = new EncogWriteHelper(os);
final SOM som = (SOM) obj;
out.addSection("SOM");
out.addSubSection("PARAMS");
out.addProperties(som.getProperties());
out.addSubSection("NETWORK");
out.writeProperty(PersistConst.WEIGHTS, som.getWeights());
out.writeProperty(PersistConst.INPUT_COUNT, som.getInputCount());
out.writeProperty(PersistConst.OUTPUT_COUNT, som.getOutputNeuronCount());
out.flush();
}
/**
* Save a subsection.
*
* @param out The output file.
* @param section The section.
* @param subSection The subsection.
*/
private void saveSubSection(
final EncogWriteHelper out, final String section, final String subSection) {
if (!section.equals(out.getCurrentSection())) {
out.addSection(section);
}
out.addSubSection(subSection);
final List<PropertyEntry> list =
PropertyConstraints.getInstance().getEntries(section, subSection);
Collections.sort(list);
for (final PropertyEntry entry : list) {
final String key = section + ":" + subSection + "_" + entry.getName();
final String value = this.script.getProperties().getPropertyString(key);
if (value != null) {
out.writeProperty(entry.getName(), value);
} else {
out.writeProperty(entry.getName(), "");
}
}
}
/**
* Save the script to a stream.
*
* @param stream The output stream.
*/
public final void save(final OutputStream stream) {
final EncogWriteHelper out = new EncogWriteHelper(stream);
saveSubSection(out, "HEADER", "DATASOURCE");
saveConfig(out);
if (this.script.getFields() != null) {
saveData(out);
saveNormalize(out);
}
saveSubSection(out, "RANDOMIZE", "CONFIG");
saveSubSection(out, "CLUSTER", "CONFIG");
saveSubSection(out, "BALANCE", "CONFIG");
if (this.script.getSegregate().getSegregateTargets() != null) {
saveSegregate(out);
}
saveSubSection(out, "GENERATE", "CONFIG");
saveMachineLearning(out);
saveTasks(out);
out.flush();
}
/** {@inheritDoc} */
@Override
public final void save(final OutputStream os, final Object obj) {
final EncogWriteHelper out = new EncogWriteHelper(os);
final BAM bam = (BAM) obj;
out.addSection("BAM");
out.addSubSection("PARAMS");
out.addProperties(bam.getProperties());
out.addSubSection("NETWORK");
out.writeProperty(PersistConst.PROPERTY_F1_COUNT, bam.getF1Count());
out.writeProperty(PersistConst.PROPERTY_F2_COUNT, bam.getF2Count());
out.writeProperty(PersistConst.PROPERTY_WEIGHTS_F1_F2, bam.getWeightsF1toF2());
out.writeProperty(PersistConst.PROPERTY_WEIGHTS_F2_F1, bam.getWeightsF2toF1());
out.flush();
}
/**
* 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();
}
}
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();
}
}
}
@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 final void save(final OutputStream os, final Object obj) {
final EncogWriteHelper out = new EncogWriteHelper(os);
final CPN cpn = (CPN) obj;
out.addSection("CPN");
out.addSubSection("PARAMS");
out.addProperties(cpn.getProperties());
out.addSubSection("NETWORK");
out.writeProperty(PersistConst.INPUT_COUNT, cpn.getInputCount());
out.writeProperty(PersistConst.INSTAR, cpn.getInstarCount());
out.writeProperty(PersistConst.OUTPUT_COUNT, cpn.getOutputCount());
out.writeProperty(PersistCPN.PROPERTY_inputToInstar, cpn.getWeightsInputToInstar());
out.writeProperty(PersistCPN.PROPERTY_instarToInput, cpn.getWeightsInstarToOutstar());
out.writeProperty(PersistCPN.PROPERTY_winnerCount, cpn.getWinnerCount());
out.flush();
}
/** {@inheritDoc} */
@Override
public void save(final OutputStream os, final Object obj) {
final EncogWriteHelper out = new EncogWriteHelper(os);
final ART1 art1 = (ART1) obj;
out.addSection("ART1");
out.addSubSection("PARAMS");
out.addProperties(art1.getProperties());
out.addSubSection("NETWORK");
out.writeProperty(ART.PROPERTY_A1, art1.getA1());
out.writeProperty(ART.PROPERTY_B1, art1.getB1());
out.writeProperty(ART.PROPERTY_C1, art1.getC1());
out.writeProperty(ART.PROPERTY_D1, art1.getD1());
out.writeProperty(PersistConst.PROPERTY_F1_COUNT, art1.getF1Count());
out.writeProperty(PersistConst.PROPERTY_F2_COUNT, art1.getF2Count());
out.writeProperty(ART.PROPERTY_NO_WINNER, art1.getNoWinner());
out.writeProperty(ART.PROPERTY_L, art1.getL());
out.writeProperty(ART.PROPERTY_VIGILANCE, art1.getVigilance());
out.writeProperty(PersistConst.PROPERTY_WEIGHTS_F1_F2, art1.getWeightsF1toF2());
out.writeProperty(PersistConst.PROPERTY_WEIGHTS_F2_F1, art1.getWeightsF2toF1());
out.flush();
}
/**
* 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();
}
}
}
}
public void saveConfig() {
File file = null;
try {
String home = System.getProperty("user.home");
file = new File(home, EncogWorkBench.CONFIG_FILENAME);
OutputStream os = new FileOutputStream(file);
EncogWriteHelper out = new EncogWriteHelper(os);
out.addSection("ENCOG");
out.addSubSection("TRAINING");
out.writeProperty(EncogWorkBenchConfig.PROPERTY_DEFAULT_ERROR, this.defaultError);
out.writeProperty(EncogWorkBenchConfig.PROPERTY_THREAD_COUNT, this.threadCount);
out.writeProperty(EncogWorkBenchConfig.PROPERTY_USE_GPU, this.useOpenCL);
out.writeProperty(EncogWorkBenchConfig.PROPERTY_ERROR_CALC, this.errorCalculation);
out.writeProperty(EncogWorkBenchConfig.PROPERTY_STEP_COUNT, this.iterationStepCount);
out.writeProperty(EncogWorkBenchConfig.PROPERTY_TRAINING_HISTORY, this.trainingHistory);
out.writeProperty(
EncogWorkBenchConfig.PROPERTY_TRAINING_IMPROVEMENT, this.showTrainingImprovement);
out.writeProperty(EncogWorkBenchConfig.PROPERTY_LOG_LEVEL, getLogLevel());
out.addSubSection("PATHS");
out.writeProperty(EncogWorkBenchConfig.PROPERTY_PROJECT_ROOT, this.projectRoot);
out.flush();
os.close();
} catch (IOException ex) {
if (file != null) EncogWorkBench.displayError("Can't write config file", file.toString());
}
}
/**
* 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();
}
}
/** {@inheritDoc} */
@Override
public final void save(final OutputStream os, final Object obj) {
final EncogWriteHelper out = new EncogWriteHelper(os);
final BayesianNetwork b = (BayesianNetwork) obj;
out.addSection("BAYES-NETWORK");
out.addSubSection("BAYES-PARAM");
String queryType = "";
String queryStr = b.getClassificationStructure();
if (b.getQuery() != null) {
queryType = b.getQuery().getClass().getSimpleName();
}
out.writeProperty("queryType", queryType);
out.writeProperty("query", queryStr);
out.writeProperty("contents", b.getContents());
out.addSubSection("BAYES-PROPERTIES");
out.addProperties(b.getProperties());
out.addSubSection("BAYES-TABLE");
for (BayesianEvent event : b.getEvents()) {
for (TableLine line : event.getTable().getLines()) {
if (line == null) continue;
StringBuilder str = new StringBuilder();
str.append("P(");
str.append(BayesianEvent.formatEventName(event, line.getResult()));
if (event.getParents().size() > 0) {
str.append("|");
}
int index = 0;
boolean first = true;
for (BayesianEvent parentEvent : event.getParents()) {
if (!first) {
str.append(",");
}
first = false;
int arg = line.getArguments()[index++];
if (parentEvent.isBoolean()) {
if (arg == 0) {
str.append("+");
} else {
str.append("-");
}
}
str.append(parentEvent.getLabel());
if (!parentEvent.isBoolean()) {
str.append("=");
if (arg >= parentEvent.getChoices().size()) {
throw new BayesianError(
"Argument value " + arg + " is out of range for event " + parentEvent.toString());
}
str.append(parentEvent.getChoice(arg));
}
}
str.append(")=");
str.append(line.getProbability());
str.append("\n");
out.write(str.toString());
}
}
out.flush();
}
/** {@inheritDoc} */
@Override
public void save(final OutputStream os, final Object obj) {
final EncogWriteHelper out = new EncogWriteHelper(os);
final BoltzmannMachine boltz = (BoltzmannMachine) obj;
out.addSection("BOLTZMANN");
out.addSubSection("PARAMS");
out.addProperties(boltz.getProperties());
out.addSubSection("NETWORK");
out.writeProperty(PersistConst.WEIGHTS, boltz.getWeights());
out.writeProperty(PersistConst.OUTPUT, boltz.getCurrentState().getData());
out.writeProperty(PersistConst.NEURON_COUNT, boltz.getNeuronCount());
out.writeProperty(PersistConst.THRESHOLDS, boltz.getThreshold());
out.writeProperty(BoltzmannMachine.ANNEAL_CYCLES, boltz.getAnnealCycles());
out.writeProperty(BoltzmannMachine.RUN_CYCLES, boltz.getRunCycles());
out.writeProperty(PersistConst.TEMPERATURE, boltz.getTemperature());
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();
}
/** {@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();
}
