/** * Add a line. * * @param l * The line to add. */ public final void addLine(final String l) { if (this.line.length() > 0) { writeLine(); } this.out.println(l); }
private void saveProcess(EncogWriteHelper out) { saveSubSection(out, "PROCESS", "CONFIG"); out.addSubSection("FIELDS"); out.addColumn("name"); out.addColumn("command"); out.writeLine(); for (final ProcessField field : this.script.getProcess().getFields()) { out.addColumn(field.getName()); out.addColumn(field.getCommand()); out.writeLine(); } 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(); } }
/** * Save the ML sections. * * @param out * The output file. */ private void saveMachineLearning(final EncogWriteHelper out) { saveSubSection(out, "ML", "CONFIG"); saveSubSection(out, "ML", "TRAIN"); out.addSubSection("OPCODES"); out.addColumn("code"); out.addColumn("count"); out.writeLine(); for( final ScriptOpcode so: this.script.getOpcodes() ) { out.addColumn(so.getName()); out.addColumn(so.getArgCount()); out.writeLine(); } }
out.addColumn(temp.getName()); out.addColumn(temp.getChildNodeCount()); out.writeLine(); out.addColumn("enum_type"); out.addColumn("enum_count"); out.writeLine(); out.addColumn(pop.getContext().getResult().getEnumType()); out.addColumn(pop.getContext().getResult().getEnumValueCount()); out.writeLine(); out.addColumn(mapping.getEnumType()); out.addColumn(mapping.getEnumValueCount()); out.writeLine(); out.addColumn(species.getBestScore()); out.addColumn(species.getGensNoImprovement()); out.writeLine(); for (final Genome genome : species.getMembers()) { final EncogProgram prg = (EncogProgram) genome; out.writeLine();
out.addColumn(species.getBestScore()); out.addColumn(species.getGensNoImprovement()); out.writeLine(); out.addColumn(neatGenome.getScore()); out.addColumn(neatGenome.getBirthGeneration()); out.writeLine(); .neuronTypeToString(neatNeuronGene.getNeuronType())); out.addColumn(neatNeuronGene.getInnovationId()); out.writeLine(); out.addColumn(neatLinkGene.getWeight()); out.addColumn(neatLinkGene.getInnovationId()); out.writeLine();
out.addColumn("sdev"); out.addColumn("source"); out.writeLine(); out.addColumn(field.getStandardDeviation()); out.addColumn(field.getSource()); out.writeLine(); out.addColumn("name"); out.addColumn("count"); out.writeLine(); out.addColumn(col.getName()); out.addColumn(col.getCount()); out.writeLine();
out.addColumn(af.getParams()[i]); out.writeLine();
out.addColumn(innovation.getInnovationID()); out.addColumn(innovation.getNeuronID()); out.writeLine();
out.addColumn(af.getParams()[i]); out.writeLine();
out.addColumn(pair.getIdeal().getData(i)); out.writeLine();