/** {@inheritDoc} */
@Override
public final void write(final double[] input, final double[] ideal, final double significance) {
final StringBuilder builder = new StringBuilder();
builder.append("1");
builder.append(":");
builder.append(this.inputCount + this.idealCount);
this.xmlOut.addAttribute("spans", builder.toString());
this.xmlOut.addAttribute("r", "" + (this.row++));
this.xmlOut.beginTag("row");
int index = 0;
for (int i = 0; i < this.inputCount; i++) {
this.xmlOut.addAttribute("r", toColumn(index++));
this.xmlOut.beginTag("c");
this.xmlOut.beginTag("v");
this.xmlOut.addText(CSVFormat.EG_FORMAT.format(input[i], Encog.DEFAULT_PRECISION));
this.xmlOut.endTag();
this.xmlOut.endTag();
}
for (int i = 0; i < this.idealCount; i++) {
this.xmlOut.addAttribute("r", toColumn(index++));
this.xmlOut.beginTag("c");
this.xmlOut.beginTag("v");
this.xmlOut.addText(CSVFormat.EG_FORMAT.format(ideal[i], Encog.DEFAULT_PRECISION));
this.xmlOut.endTag();
this.xmlOut.endTag();
}
this.xmlOut.endTag();
}
/**
* Generate a table, in BIF format.
*
* @param event The event to write.
* @return The string form of the table.
*/
public static String generateTable(BayesianEvent event) {
StringBuilder s = new StringBuilder();
int tableIndex = 0;
int[] args = new int[event.getParents().size()];
do {
for (int result = 0; result < event.getChoices().size(); result++) {
TableLine line = event.getTable().findLine(result, args);
if (s.length() > 0) {
s.append(" ");
}
s.append(CSVFormat.EG_FORMAT.format(line.getProbability(), Encog.DEFAULT_PRECISION));
}
} while (BIFUtil.rollArgs(event, args));
return s.toString();
}
private String renderNode(ProgramNode node) {
StringBuilder result = new StringBuilder();
for (int i = 0; i < node.getChildNodes().size(); i++) {
ProgramNode childNode = node.getChildNode(i);
result.append(renderNode(childNode));
}
result.append('[');
result.append(node.getName());
result.append(':');
result.append(node.getTemplate().getChildNodeCount());
for (int i = 0; i < node.getTemplate().getDataSize(); i++) {
result.append(':');
ValueType t = node.getData()[i].getExpressionType();
if (t == ValueType.booleanType) {
result.append(node.getData()[i].toBooleanValue() ? 't' : 'f');
} else if (t == ValueType.floatingType) {
result.append(
CSVFormat.EG_FORMAT.format(node.getData()[i].toFloatValue(), Encog.DEFAULT_PRECISION));
} else if (t == ValueType.intType) {
result.append(node.getData()[i].toIntValue());
} else if (t == ValueType.enumType) {
result.append(node.getData()[i].getEnumType());
result.append("#");
result.append(node.getData()[i].toIntValue());
} else if (t == ValueType.stringType) {
result.append("\"");
result.append(node.getData()[i].toStringValue());
result.append("\"");
}
}
result.append(']');
return result.toString().trim();
}
/**
* Define a probability.
*
* @param line The line to define the probability.
*/
public void defineProbability(String line) {
int index = line.lastIndexOf('=');
boolean error = false;
double prob = 0.0;
String left = "";
String right = "";
if (index != -1) {
left = line.substring(0, index);
right = line.substring(index + 1);
try {
prob = CSVFormat.EG_FORMAT.parse(right);
} catch (NumberFormatException ex) {
error = true;
}
}
if (error || index == -1) {
throw new BayesianError(
"Probability must be of the form \"P(event|condition1,condition2,etc.)=0.5\". Conditions are optional.");
}
defineProbability(left, prob);
}
/**
* Set a property as a double.
*
* @param name The name of the property.
* @param d The value of the property.
*/
@Override
public void setProperty(final String name, final double d) {
this.properties.put(name, "" + CSVFormat.EG_FORMAT.format(d, Encog.DEFAULT_PRECISION));
updateProperties();
}
/** {@inheritDoc} */
@Override
public Object read(final InputStream is) {
final BasicNetwork result = new BasicNetwork();
final FlatNetwork flat = new FlatNetwork();
final EncogReadHelper in = new EncogReadHelper(is);
EncogFileSection section;
while ((section = in.readNextSection()) != null) {
if (section.getSectionName().equals("BASIC")
&& section.getSubSectionName().equals("PARAMS")) {
final Map<String, String> params = section.parseParams();
result.getProperties().putAll(params);
}
if (section.getSectionName().equals("BASIC")
&& section.getSubSectionName().equals("NETWORK")) {
final Map<String, String> params = section.parseParams();
flat.setBeginTraining(EncogFileSection.parseInt(params, BasicNetwork.TAG_BEGIN_TRAINING));
flat.setConnectionLimit(
EncogFileSection.parseDouble(params, BasicNetwork.TAG_CONNECTION_LIMIT));
flat.setContextTargetOffset(
EncogFileSection.parseIntArray(params, BasicNetwork.TAG_CONTEXT_TARGET_OFFSET));
flat.setContextTargetSize(
EncogFileSection.parseIntArray(params, BasicNetwork.TAG_CONTEXT_TARGET_SIZE));
flat.setEndTraining(EncogFileSection.parseInt(params, BasicNetwork.TAG_END_TRAINING));
flat.setHasContext(EncogFileSection.parseBoolean(params, BasicNetwork.TAG_HAS_CONTEXT));
flat.setInputCount(EncogFileSection.parseInt(params, PersistConst.INPUT_COUNT));
flat.setLayerCounts(EncogFileSection.parseIntArray(params, BasicNetwork.TAG_LAYER_COUNTS));
flat.setLayerFeedCounts(
EncogFileSection.parseIntArray(params, BasicNetwork.TAG_LAYER_FEED_COUNTS));
flat.setLayerContextCount(
EncogFileSection.parseIntArray(params, BasicNetwork.TAG_LAYER_CONTEXT_COUNT));
flat.setLayerIndex(EncogFileSection.parseIntArray(params, BasicNetwork.TAG_LAYER_INDEX));
flat.setLayerOutput(section.parseDoubleArray(params, PersistConst.OUTPUT));
flat.setLayerSums(new double[flat.getLayerOutput().length]);
flat.setOutputCount(EncogFileSection.parseInt(params, PersistConst.OUTPUT_COUNT));
flat.setWeightIndex(EncogFileSection.parseIntArray(params, BasicNetwork.TAG_WEIGHT_INDEX));
flat.setWeights(section.parseDoubleArray(params, PersistConst.WEIGHTS));
flat.setBiasActivation(section.parseDoubleArray(params, BasicNetwork.TAG_BIAS_ACTIVATION));
} else if (section.getSectionName().equals("BASIC")
&& section.getSubSectionName().equals("ACTIVATION")) {
int index = 0;
flat.setActivationFunctions(new ActivationFunction[flat.getLayerCounts().length]);
for (final String line : section.getLines()) {
ActivationFunction af = null;
final List<String> cols = EncogFileSection.splitColumns(line);
// if this is a class name with a path, then do not default to inside of the Encog
// package.
String name;
if (cols.get(0).indexOf('.') != -1) {
name = cols.get(0);
} else {
name = "org.encog.engine.network.activation." + cols.get(0);
}
try {
final Class<?> clazz = Class.forName(name);
af = (ActivationFunction) clazz.newInstance();
} catch (final ClassNotFoundException e) {
throw new PersistError(e);
} catch (final InstantiationException e) {
throw new PersistError(e);
} catch (final IllegalAccessException e) {
throw new PersistError(e);
}
for (int i = 0; i < af.getParamNames().length; i++) {
af.setParam(i, CSVFormat.EG_FORMAT.parse(cols.get(i + 1)));
}
flat.getActivationFunctions()[index++] = af;
}
}
}
result.getStructure().setFlat(flat);
result.updateProperties();
return result;
}
@Override
public Object read(final InputStream is) {
long nextInnovationID = 0;
long nextGeneID = 0;
final NEATPopulation result = new NEATPopulation();
final NEATInnovationList innovationList = new NEATInnovationList();
innovationList.setPopulation(result);
result.setInnovations(innovationList);
final EncogReadHelper in = new EncogReadHelper(is);
EncogFileSection section;
while ((section = in.readNextSection()) != null) {
if (section.getSectionName().equals("NEAT-POPULATION")
&& section.getSubSectionName().equals("INNOVATIONS")) {
for (final String line : section.getLines()) {
final List<String> cols = EncogFileSection.splitColumns(line);
final NEATInnovation innovation = new NEATInnovation();
final int innovationID = Integer.parseInt(cols.get(1));
innovation.setInnovationID(innovationID);
innovation.setNeuronID(Integer.parseInt(cols.get(2)));
result.getInnovations().getInnovations().put(cols.get(0), innovation);
nextInnovationID = Math.max(nextInnovationID, innovationID + 1);
}
} else if (section.getSectionName().equals("NEAT-POPULATION")
&& section.getSubSectionName().equals("SPECIES")) {
NEATGenome lastGenome = null;
BasicSpecies lastSpecies = null;
for (final String line : section.getLines()) {
final List<String> cols = EncogFileSection.splitColumns(line);
if (cols.get(0).equalsIgnoreCase("s")) {
lastSpecies = new BasicSpecies();
lastSpecies.setPopulation(result);
lastSpecies.setAge(Integer.parseInt(cols.get(1)));
lastSpecies.setBestScore(CSVFormat.EG_FORMAT.parse(cols.get(2)));
lastSpecies.setGensNoImprovement(Integer.parseInt(cols.get(3)));
result.getSpecies().add(lastSpecies);
} else if (cols.get(0).equalsIgnoreCase("g")) {
final boolean isLeader = lastGenome == null;
lastGenome = new NEATGenome();
lastGenome.setInputCount(result.getInputCount());
lastGenome.setOutputCount(result.getOutputCount());
lastGenome.setSpecies(lastSpecies);
lastGenome.setAdjustedScore(CSVFormat.EG_FORMAT.parse(cols.get(1)));
lastGenome.setScore(CSVFormat.EG_FORMAT.parse(cols.get(2)));
lastGenome.setBirthGeneration(Integer.parseInt(cols.get(3)));
lastSpecies.add(lastGenome);
if (isLeader) {
lastSpecies.setLeader(lastGenome);
}
} else if (cols.get(0).equalsIgnoreCase("n")) {
final NEATNeuronGene neuronGene = new NEATNeuronGene();
final int geneID = Integer.parseInt(cols.get(1));
neuronGene.setId(geneID);
final ActivationFunction af = EncogFileSection.parseActivationFunction(cols.get(2));
neuronGene.setActivationFunction(af);
neuronGene.setNeuronType(PersistNEATPopulation.stringToNeuronType(cols.get(3)));
neuronGene.setInnovationId(Integer.parseInt(cols.get(4)));
lastGenome.getNeuronsChromosome().add(neuronGene);
nextGeneID = Math.max(geneID + 1, nextGeneID);
} else if (cols.get(0).equalsIgnoreCase("l")) {
final NEATLinkGene linkGene = new NEATLinkGene();
linkGene.setId(Integer.parseInt(cols.get(1)));
linkGene.setEnabled(Integer.parseInt(cols.get(2)) > 0);
linkGene.setFromNeuronID(Integer.parseInt(cols.get(3)));
linkGene.setToNeuronID(Integer.parseInt(cols.get(4)));
linkGene.setWeight(CSVFormat.EG_FORMAT.parse(cols.get(5)));
linkGene.setInnovationId(Integer.parseInt(cols.get(6)));
lastGenome.getLinksChromosome().add(linkGene);
}
}
} else if (section.getSectionName().equals("NEAT-POPULATION")
&& section.getSubSectionName().equals("CONFIG")) {
final Map<String, String> params = section.parseParams();
final String afStr = params.get(NEATPopulation.PROPERTY_NEAT_ACTIVATION);
if (afStr.equalsIgnoreCase(PersistNEATPopulation.TYPE_CPPN)) {
HyperNEATGenome.buildCPPNActivationFunctions(result.getActivationFunctions());
} else {
result.setNEATActivationFunction(
EncogFileSection.parseActivationFunction(
params, NEATPopulation.PROPERTY_NEAT_ACTIVATION));
}
result.setActivationCycles(
EncogFileSection.parseInt(params, PersistConst.ACTIVATION_CYCLES));
result.setInputCount(EncogFileSection.parseInt(params, PersistConst.INPUT_COUNT));
result.setOutputCount(EncogFileSection.parseInt(params, PersistConst.OUTPUT_COUNT));
result.setPopulationSize(
EncogFileSection.parseInt(params, NEATPopulation.PROPERTY_POPULATION_SIZE));
result.setSurvivalRate(
EncogFileSection.parseDouble(params, NEATPopulation.PROPERTY_SURVIVAL_RATE));
result.setActivationCycles(
EncogFileSection.parseInt(params, NEATPopulation.PROPERTY_CYCLES));
}
}
// set factories
if (result.isHyperNEAT()) {
result.setGenomeFactory(new FactorHyperNEATGenome());
result.setCODEC(new HyperNEATCODEC());
} else {
result.setGenomeFactory(new FactorNEATGenome());
result.setCODEC(new NEATCODEC());
}
// set the next ID's
result.getInnovationIDGenerate().setCurrentID(nextInnovationID);
result.getGeneIDGenerate().setCurrentID(nextGeneID);
// find first genome, which should be the best genome
if (result.getSpecies().size() > 0) {
final Species species = result.getSpecies().get(0);
if (species.getMembers().size() > 0) {
result.setBestGenome(species.getMembers().get(0));
}
}
return result;
}
/** {@inheritDoc} */
@Override
public Object read(final InputStream is) {
final RBFNetwork result = new RBFNetwork();
final FlatNetworkRBF flat = (FlatNetworkRBF) result.getFlat();
final EncogReadHelper in = new EncogReadHelper(is);
EncogFileSection section;
while ((section = in.readNextSection()) != null) {
if (section.getSectionName().equals("RBF-NETWORK")
&& section.getSubSectionName().equals("PARAMS")) {
final Map<String, String> params = section.parseParams();
result.getProperties().putAll(params);
}
if (section.getSectionName().equals("RBF-NETWORK")
&& section.getSubSectionName().equals("NETWORK")) {
final Map<String, String> params = section.parseParams();
flat.setBeginTraining(EncogFileSection.parseInt(params, BasicNetwork.TAG_BEGIN_TRAINING));
flat.setConnectionLimit(
EncogFileSection.parseDouble(params, BasicNetwork.TAG_CONNECTION_LIMIT));
flat.setContextTargetOffset(
EncogFileSection.parseIntArray(params, BasicNetwork.TAG_CONTEXT_TARGET_OFFSET));
flat.setContextTargetSize(
EncogFileSection.parseIntArray(params, BasicNetwork.TAG_CONTEXT_TARGET_SIZE));
flat.setEndTraining(EncogFileSection.parseInt(params, BasicNetwork.TAG_END_TRAINING));
flat.setHasContext(EncogFileSection.parseBoolean(params, BasicNetwork.TAG_HAS_CONTEXT));
flat.setInputCount(EncogFileSection.parseInt(params, PersistConst.INPUT_COUNT));
flat.setLayerCounts(EncogFileSection.parseIntArray(params, BasicNetwork.TAG_LAYER_COUNTS));
flat.setLayerFeedCounts(
EncogFileSection.parseIntArray(params, BasicNetwork.TAG_LAYER_FEED_COUNTS));
flat.setLayerContextCount(
EncogFileSection.parseIntArray(params, BasicNetwork.TAG_LAYER_CONTEXT_COUNT));
flat.setLayerIndex(EncogFileSection.parseIntArray(params, BasicNetwork.TAG_LAYER_INDEX));
flat.setLayerOutput(section.parseDoubleArray(params, PersistConst.OUTPUT));
flat.setLayerSums(new double[flat.getLayerOutput().length]);
flat.setOutputCount(EncogFileSection.parseInt(params, PersistConst.OUTPUT_COUNT));
flat.setWeightIndex(EncogFileSection.parseIntArray(params, BasicNetwork.TAG_WEIGHT_INDEX));
flat.setWeights(section.parseDoubleArray(params, PersistConst.WEIGHTS));
flat.setBiasActivation(section.parseDoubleArray(params, BasicNetwork.TAG_BIAS_ACTIVATION));
} else if (section.getSectionName().equals("RBF-NETWORK")
&& section.getSubSectionName().equals("ACTIVATION")) {
int index = 0;
flat.setActivationFunctions(new ActivationFunction[flat.getLayerCounts().length]);
for (final String line : section.getLines()) {
ActivationFunction af = null;
final List<String> cols = EncogFileSection.splitColumns(line);
final String name = "org.encog.engine.network.activation." + cols.get(0);
try {
final Class<?> clazz = Class.forName(name);
af = (ActivationFunction) clazz.newInstance();
} catch (final ClassNotFoundException e) {
throw new PersistError(e);
} catch (final InstantiationException e) {
throw new PersistError(e);
} catch (final IllegalAccessException e) {
throw new PersistError(e);
}
for (int i = 0; i < af.getParamNames().length; i++) {
af.setParam(i, CSVFormat.EG_FORMAT.parse(cols.get(i + 1)));
}
flat.getActivationFunctions()[index++] = af;
}
} else if (section.getSectionName().equals("RBF-NETWORK")
&& section.getSubSectionName().equals("RBF")) {
int index = 0;
final int hiddenCount = flat.getLayerCounts()[1];
final int inputCount = flat.getLayerCounts()[2];
flat.setRBF(new RadialBasisFunction[hiddenCount]);
for (final String line : section.getLines()) {
RadialBasisFunction rbf = null;
final List<String> cols = EncogFileSection.splitColumns(line);
final String name = "org.encog.mathutil.rbf." + cols.get(0);
try {
final Class<?> clazz = Class.forName(name);
rbf = (RadialBasisFunction) clazz.newInstance();
} catch (final ClassNotFoundException e) {
throw new PersistError(e);
} catch (final InstantiationException e) {
throw new PersistError(e);
} catch (final IllegalAccessException e) {
throw new PersistError(e);
}
rbf.setWidth(CSVFormat.EG_FORMAT.parse(cols.get(1)));
rbf.setPeak(CSVFormat.EG_FORMAT.parse(cols.get(2)));
rbf.setCenters(new double[inputCount]);
for (int i = 0; i < inputCount; i++) {
rbf.getCenters()[i] = CSVFormat.EG_FORMAT.parse(cols.get(i + 3));
}
flat.getRBF()[index++] = rbf;
}
}
}
return result;
}