public AddProperties ( String>.IDictionary |
||
properties | String>.IDictionary | The properties. |
return | void |
/// <summary> /// /// </summary> /// public void Save(Stream os, Object obj) { var xout = new EncogWriteHelper(os); var hopfield = (HopfieldNetwork) obj; xout.AddSection("HOPFIELD"); xout.AddSubSection("PARAMS"); xout.AddProperties(hopfield.Properties); xout.AddSubSection("NETWORK"); xout.WriteProperty(PersistConst.Weights, hopfield.Weights); xout.WriteProperty(PersistConst.Output, hopfield.CurrentState.Data); xout.WriteProperty(PersistConst.NeuronCount, hopfield.NeuronCount); xout.Flush(); }
/// <inheritdoc/> public void Save(Stream os, Object obj) { var xout = new EncogWriteHelper(os); var net = (RBFNetwork) obj; var flat = (FlatNetworkRBF) net.Flat; xout.AddSection("RBF-NETWORK"); xout.AddSubSection("PARAMS"); xout.AddProperties(net.Properties); xout.AddSubSection("NETWORK"); xout.WriteProperty(BasicNetwork.TagBeginTraining, flat.BeginTraining); xout.WriteProperty(BasicNetwork.TagConnectionLimit, flat.ConnectionLimit); xout.WriteProperty(BasicNetwork.TagContextTargetOffset, flat.ContextTargetOffset); xout.WriteProperty(BasicNetwork.TagContextTargetSize, flat.ContextTargetSize); xout.WriteProperty(BasicNetwork.TagEndTraining, flat.EndTraining); xout.WriteProperty(BasicNetwork.TagHasContext, flat.HasContext); xout.WriteProperty(PersistConst.InputCount, flat.InputCount); xout.WriteProperty(BasicNetwork.TagLayerCounts, flat.LayerCounts); xout.WriteProperty(BasicNetwork.TagLayerFeedCounts, flat.LayerFeedCounts); xout.WriteProperty(BasicNetwork.TagLayerContextCount, flat.LayerContextCount); xout.WriteProperty(BasicNetwork.TagLayerIndex, flat.LayerIndex); xout.WriteProperty(PersistConst.Output, flat.LayerOutput); xout.WriteProperty(PersistConst.OutputCount, flat.OutputCount); xout.WriteProperty(BasicNetwork.TagWeightIndex, flat.WeightIndex); xout.WriteProperty(PersistConst.Weights, flat.Weights); xout.WriteProperty(BasicNetwork.TagBiasActivation, flat.BiasActivation); xout.AddSubSection("ACTIVATION"); foreach (IActivationFunction af in flat.ActivationFunctions) { xout.AddColumn(af.GetType().Name); foreach (double t in af.Params) { xout.AddColumn(t); } xout.WriteLine(); } xout.AddSubSection("RBF"); foreach (IRadialBasisFunction rbf in flat.RBF) { xout.AddColumn(rbf.GetType().Name); xout.AddColumn(rbf.Width); xout.AddColumn(rbf.Peak); foreach (double t in rbf.Centers) { xout.AddColumn(t); } xout.WriteLine(); } xout.Flush(); }
/// <inheritdoc/> public void Save(Stream os, Object obj) { EncogWriteHelper o = new EncogWriteHelper(os); BayesianNetwork b = (BayesianNetwork)obj; o.AddSection("BAYES-NETWORK"); o.AddSubSection("BAYES-PARAM"); String queryType = ""; String queryStr = b.ClassificationStructure; if (b.Query != null) { queryType = b.Query.GetType().Name; } o.WriteProperty("queryType", queryType); o.WriteProperty("query", queryStr); o.WriteProperty("contents", b.Contents); o.AddSubSection("BAYES-PROPERTIES"); o.AddProperties(b.Properties); o.AddSubSection("BAYES-TABLE"); foreach (BayesianEvent e in b.Events) { foreach (TableLine line in e.Table.Lines) { if (line == null) continue; StringBuilder str = new StringBuilder(); str.Append("P("); str.Append(BayesianEvent.FormatEventName(e, line.Result)); if (e.Parents.Count > 0) { str.Append("|"); } int index = 0; bool first = true; foreach (BayesianEvent parentEvent in e.Parents) { if (!first) { str.Append(","); } first = false; int arg = line.Arguments[index++]; if (parentEvent.IsBoolean) { if (arg == 0) { str.Append("+"); } else { str.Append("-"); } } str.Append(parentEvent.Label); if (!parentEvent.IsBoolean) { str.Append("="); if (arg >= parentEvent.Choices.Count) { throw new BayesianError("Argument value " + arg + " is out of range for event " + parentEvent.ToString()); } str.Append(parentEvent.GetChoice(arg)); } } str.Append(")="); str.Append(line.Probability); str.Append("\n"); o.Write(str.ToString()); } } o.Flush(); }
public void Save(Stream os, object obj) { BasicNetwork network; FlatNetwork flat; IActivationFunction function; int num; IActivationFunction[] activationFunctions; int num2; EncogWriteHelper helper = new EncogWriteHelper(os); if ((((uint) num2) + ((uint) num)) >= 0) { goto Label_0290; } goto Label_0059; Label_0024: if (num < function.Params.Length) { helper.AddColumn(function.Params[num]); goto Label_0080; } if (-1 == 0) { goto Label_00CC; } helper.WriteLine(); Label_0040: num2++; Label_0046: if (num2 < activationFunctions.Length) { goto Label_00F8; } helper.Flush(); goto Label_0071; Label_0059: num++; if (((uint) num2) <= uint.MaxValue) { goto Label_0024; } Label_0071: if (1 != 0) { return; } goto Label_0290; Label_0080: if ((((uint) num2) + ((uint) num)) < 0) { goto Label_0135; } goto Label_0059; Label_00CC: helper.WriteProperty("biasActivation", flat.BiasActivation); helper.AddSubSection("ACTIVATION"); activationFunctions = flat.ActivationFunctions; num2 = 0; goto Label_0046; Label_00F8: function = activationFunctions[num2]; if (((uint) num2) >= 0) { helper.AddColumn(function.GetType().Name); } if (0x7fffffff != 0) { num = 0; goto Label_0024; } goto Label_0080; Label_0135: helper.WriteProperty("outputCount", flat.OutputCount); if ((((uint) num) & 0) != 0) { goto Label_00F8; } helper.WriteProperty("weightIndex", flat.WeightIndex); helper.WriteProperty("weights", flat.Weights); goto Label_00CC; Label_0290: network = (BasicNetwork) obj; flat = network.Structure.Flat; helper.AddSection("BASIC"); helper.AddSubSection("PARAMS"); helper.AddProperties(network.Properties); if (((uint) num2) < 0) { goto Label_0040; } helper.AddSubSection("NETWORK"); helper.WriteProperty("beginTraining", flat.BeginTraining); helper.WriteProperty("connectionLimit", flat.ConnectionLimit); helper.WriteProperty("contextTargetOffset", flat.ContextTargetOffset); helper.WriteProperty("contextTargetSize", flat.ContextTargetSize); helper.WriteProperty("endTraining", flat.EndTraining); helper.WriteProperty("hasContext", flat.HasContext); helper.WriteProperty("inputCount", flat.InputCount); helper.WriteProperty("layerCounts", flat.LayerCounts); helper.WriteProperty("layerFeedCounts", flat.LayerFeedCounts); helper.WriteProperty("layerContextCount", flat.LayerContextCount); helper.WriteProperty("layerIndex", flat.LayerIndex); if (0 != 0) { goto Label_00CC; } helper.WriteProperty("output", flat.LayerOutput); goto Label_0135; }
/// <inheritdoc/> public void Save(Stream os, Object obj) { var xout = new EncogWriteHelper(os); var cpn = (CPNNetwork) obj; xout.AddSection("CPN"); xout.AddSubSection("PARAMS"); xout.AddProperties(cpn.Properties); xout.AddSubSection("NETWORK"); xout.WriteProperty(PersistConst.InputCount, cpn.InputCount); xout.WriteProperty(PersistConst.Instar, cpn.InstarCount); xout.WriteProperty(PersistConst.OutputCount, cpn.OutputCount); xout.WriteProperty(PropertyInputToInstar, cpn.WeightsInputToInstar); xout.WriteProperty(PropertyInstarToInput, cpn.WeightsInstarToOutstar); xout.WriteProperty(PropertyWinnerCount, cpn.WinnerCount); xout.Flush(); }
public void Save(Stream os, object obj) { ART1 art; EncogWriteHelper helper = new EncogWriteHelper(os); goto Label_010B; Label_000C: helper.Flush(); if (2 != 0) { return; } Label_0019: helper.WriteProperty("noWinner", art.NoWinner); do { helper.WriteProperty("L", art.L); } while (0 != 0); helper.WriteProperty("VIGILANCE", art.Vigilance); helper.WriteProperty("weightsF1F2", art.WeightsF1ToF2); helper.WriteProperty("weightsF2F1", art.WeightsF2ToF1); goto Label_000C; Label_010B: art = (ART1) obj; if (0 == 0) { helper.AddSection("ART1"); helper.AddSubSection("PARAMS"); if (0 == 0) { helper.AddProperties(art.Properties); helper.AddSubSection("NETWORK"); helper.WriteProperty("A1", art.A1); } helper.WriteProperty("B1", art.B1); helper.WriteProperty("C1", art.C1); if (0 != 0) { goto Label_000C; } helper.WriteProperty("D1", art.D1); helper.WriteProperty("f1Count", art.F1Count); } helper.WriteProperty("f2Count", art.F2Count); if (3 != 0) { if (0 != 0) { return; } goto Label_0019; } goto Label_010B; }
/// <summary> /// /// </summary> /// public void Save(Stream os, Object obj) { var xout = new EncogWriteHelper(os); var bam = (BAMNetwork) obj; xout.AddSection("BAM"); xout.AddSubSection("PARAMS"); xout.AddProperties(bam.Properties); xout.AddSubSection("NETWORK"); xout.WriteProperty(PersistConst.PropertyF1Count, bam.F1Count); xout.WriteProperty(PersistConst.PropertyF2Count, bam.F2Count); xout.WriteProperty(PersistConst.PropertyWeightsF1F2, bam.WeightsF1ToF2); xout.WriteProperty(PersistConst.PropertyWeightsF2F1, bam.WeightsF2ToF1); xout.Flush(); }
/// <inheritdoc/> public void Save(Stream os, Object obj) { var xout = new EncogWriteHelper(os); var net = (BasicNetwork) obj; FlatNetwork flat = net.Structure.Flat; xout.AddSection("BASIC"); xout.AddSubSection("PARAMS"); xout.AddProperties(net.Properties); xout.AddSubSection("NETWORK"); xout.WriteProperty(BasicNetwork.TagBeginTraining, flat.BeginTraining); xout.WriteProperty(BasicNetwork.TagConnectionLimit, flat.ConnectionLimit); xout.WriteProperty(BasicNetwork.TagContextTargetOffset, flat.ContextTargetOffset); xout.WriteProperty(BasicNetwork.TagContextTargetSize, flat.ContextTargetSize); xout.WriteProperty(BasicNetwork.TagEndTraining, flat.EndTraining); xout.WriteProperty(BasicNetwork.TagHasContext, flat.HasContext); xout.WriteProperty(PersistConst.InputCount, flat.InputCount); xout.WriteProperty(BasicNetwork.TagLayerCounts, flat.LayerCounts); xout.WriteProperty(BasicNetwork.TagLayerFeedCounts, flat.LayerFeedCounts); xout.WriteProperty(BasicNetwork.TagLayerContextCount, flat.LayerContextCount); xout.WriteProperty(BasicNetwork.TagLayerIndex, flat.LayerIndex); xout.WriteProperty(PersistConst.Output, flat.LayerOutput); xout.WriteProperty(PersistConst.OutputCount, flat.OutputCount); xout.WriteProperty(BasicNetwork.TagWeightIndex, flat.WeightIndex); xout.WriteProperty(PersistConst.Weights, flat.Weights); xout.WriteProperty(BasicNetwork.TagBiasActivation, flat.BiasActivation); xout.AddSubSection("ACTIVATION"); foreach (IActivationFunction af in flat.ActivationFunctions) { xout.AddColumn(af.GetType().Name); for (int i = 0; i < af.Params.Length; i++) { xout.AddColumn(af.Params[i]); } xout.WriteLine(); } xout.Flush(); }
/// <inheritdoc /> public void Save(Stream ostream, Object obj) { var writer = new EncogWriteHelper(ostream); var pop = (PrgPopulation) obj; writer.AddSection("BASIC"); writer.AddSubSection("PARAMS"); writer.AddProperties(pop.Properties); writer.AddSubSection("EPL-OPCODES"); foreach (IProgramExtensionTemplate temp in pop.Context .Functions.OpCodes) { writer.AddColumn(temp.Name); writer.AddColumn(temp.ChildNodeCount); writer.WriteLine(); } writer.AddSubSection("EPL-SYMBOLIC"); writer.AddColumn("name"); writer.AddColumn("type"); writer.AddColumn("enum"); writer.AddColumn("enum_type"); writer.AddColumn("enum_count"); writer.WriteLine(); // write the first line, the result writer.AddColumn(""); writer.AddColumn(GetType(pop.Context.Result)); writer.AddColumn(pop.Context.Result.EnumType); writer.AddColumn(pop.Context.Result.EnumValueCount); writer.WriteLine(); // write the next lines, the variables foreach (VariableMapping mapping in pop.Context.DefinedVariables) { writer.AddColumn(mapping.Name); writer.AddColumn(GetType(mapping)); writer.AddColumn(mapping.EnumType); writer.AddColumn(mapping.EnumValueCount); writer.WriteLine(); } writer.AddSubSection("EPL-POPULATION"); foreach (ISpecies species in pop.Species) { if (species.Members.Count > 0) { writer.AddColumn("s"); writer.AddColumn(species.Age); writer.AddColumn(species.BestScore); writer.AddColumn(species.GensNoImprovement); writer.WriteLine(); foreach (IGenome genome in species.Members) { var prg = (EncogProgram) genome; writer.AddColumn("p"); if (Double.IsInfinity(prg.Score) || Double.IsNaN(prg.Score)) { writer.AddColumn("NaN"); writer.AddColumn("NaN"); } else { writer.AddColumn(prg.Score); writer.AddColumn(prg.AdjustedScore); } writer.AddColumn(prg.GenerateEPL()); writer.WriteLine(); } } } writer.Flush(); }
public void Save(Stream os, object obj) { SupportVectorMachine machine; EncogWriteHelper helper = new EncogWriteHelper(os); if (8 != 0) { } Label_026A: machine = (SupportVectorMachine) obj; helper.AddSection("SVM"); if (0 == 0) { while (true) { helper.AddSubSection("PARAMS"); helper.AddProperties(machine.Properties); helper.AddSubSection("SVM-PARAM"); helper.WriteProperty("inputCount", machine.InputCount); helper.WriteProperty("C", machine.Params.C); if (0 == 0) { helper.WriteProperty("cacheSize", machine.Params.cache_size); if (-2 == 0) { goto Label_026A; } helper.WriteProperty("coef0", machine.Params.coef0); helper.WriteProperty("degree", machine.Params.degree); helper.WriteProperty("eps", machine.Params.eps); helper.WriteProperty("gamma", machine.Params.gamma); helper.WriteProperty("kernelType", machine.Params.kernel_type); } helper.WriteProperty("nrWeight", machine.Params.nr_weight); if (1 != 0) { helper.WriteProperty("nu", machine.Params.nu); helper.WriteProperty("p", machine.Params.p); helper.WriteProperty("probability", machine.Params.probability); helper.WriteProperty("shrinking", machine.Params.shrinking); helper.WriteProperty("svmType", machine.Params.svm_type); helper.WriteProperty("weight", machine.Params.weight); helper.WriteProperty("weightLabel", machine.Params.weight_label); break; } } } Label_0092: while (machine.Model != null) { helper.AddSubSection("SVM-MODEL"); try { StreamWriter writer; ASCIIEncoding encoding; MemoryStream stream = new MemoryStream(); if (1 != 0) { goto Label_005F; } Label_003E: helper.Write(encoding.GetString(stream.ToArray())); writer.Close(); stream.Close(); break; Label_005F: writer = new StreamWriter(stream); if (0 == 0) { svm.svm_save_model(writer, machine.Model); } encoding = new ASCIIEncoding(); goto Label_003E; } catch (IOException exception) { throw new PersistError(exception); } } while (true) { helper.Flush(); if (-2147483648 != 0) { return; } if (0 != 0) { goto Label_0092; } } }
/// <inheritdoc/> public void Save(Stream os, Object obj) { EncogWriteHelper writer = new EncogWriteHelper(os); HiddenMarkovModel net = (HiddenMarkovModel)obj; writer.AddSection("HMM"); writer.AddSubSection("PARAMS"); writer.AddProperties(net.Properties); writer.AddSubSection("CONFIG"); writer.WriteProperty(HiddenMarkovModel.TAG_STATES, net.StateCount); if (net.Items != null) { writer.WriteProperty(HiddenMarkovModel.TAG_ITEMS, net.Items); } writer.WriteProperty(HiddenMarkovModel.TAG_PI, net.Pi); writer.WriteProperty(HiddenMarkovModel.TAG_TRANSITION, new Matrix(net.TransitionProbability)); for (int i = 0; i < net.StateCount; i++) { writer.AddSubSection("DISTRIBUTION-" + i); IStateDistribution sd = net.StateDistributions[i]; writer.WriteProperty(HiddenMarkovModel.TAG_DIST_TYPE, sd.GetType().Name); if (sd is ContinousDistribution) { ContinousDistribution cDist = (ContinousDistribution)sd; writer.WriteProperty(HiddenMarkovModel.TAG_MEAN, cDist.Mean); writer.WriteProperty(HiddenMarkovModel.TAG_COVARIANCE, cDist.Covariance); } else if (sd is DiscreteDistribution) { DiscreteDistribution dDist = (DiscreteDistribution)sd; writer.WriteProperty(HiddenMarkovModel.TAG_PROBABILITIES, new Matrix(dDist.Probabilities)); } } writer.Flush(); }
public void Save(Stream os, object obj) { EncogWriteHelper helper = new EncogWriteHelper(os); while (true) { SOMNetwork network = (SOMNetwork) obj; helper.AddSection("SOM"); helper.AddSubSection("PARAMS"); helper.AddProperties(network.Properties); helper.AddSubSection("NETWORK"); helper.WriteProperty("weights", network.Weights); helper.WriteProperty("inputCount", network.InputCount); if (0 == 0) { helper.WriteProperty("outputCount", network.OutputCount); helper.Flush(); } if ((0 != 0) || (0 == 0)) { return; } } }
public void Save(Stream os, object obj) { IActivationFunction function; double num; IRadialBasisFunction function2; IActivationFunction[] activationFunctions; int num3; double[] @params; int num4; IRadialBasisFunction[] functionArray2; int num5; EncogWriteHelper helper = new EncogWriteHelper(os); RBFNetwork network = (RBFNetwork) obj; FlatNetworkRBF flat = (FlatNetworkRBF) network.Flat; helper.AddSection("RBF-NETWORK"); helper.AddSubSection("PARAMS"); goto Label_03F8; Label_0033: if (num5 < functionArray2.Length) { function2 = functionArray2[num5]; if (0 == 0) { helper.AddColumn(function2.GetType().Name); helper.AddColumn(function2.Width); goto Label_006E; } if ((((uint) num3) | 0x7fffffff) != 0) { goto Label_02E5; } goto Label_020D; } helper.Flush(); return; Label_006E: helper.AddColumn(function2.Peak); double[] centers = function2.Centers; int index = 0; while (index < centers.Length) { double d = centers[index]; helper.AddColumn(d); index++; } if ((((uint) index) - ((uint) num5)) <= uint.MaxValue) { helper.WriteLine(); if ((((uint) num5) - ((uint) index)) < 0) { goto Label_02A1; } num5++; goto Label_0033; } return; Label_00C6: functionArray2 = flat.RBF; num5 = 0; if ((((uint) num) - ((uint) num)) < 0) { goto Label_0125; } goto Label_0033; Label_00FA: if (num3 < activationFunctions.Length) { function = activationFunctions[num3]; goto Label_0161; } helper.AddSubSection("RBF"); if ((((uint) num5) | 15) != 0) { goto Label_01B0; } goto Label_011D; Label_0117: num4++; Label_011D: if (num4 < @params.Length) { num = @params[num4]; helper.AddColumn(num); goto Label_0117; } Label_0125: helper.WriteLine(); num3++; goto Label_00FA; Label_0161: helper.AddColumn(function.GetType().Name); @params = function.Params; Label_017A: num4 = 0; if ((((uint) num5) + ((uint) index)) > uint.MaxValue) { goto Label_03BC; } if ((((uint) num4) + ((uint) num)) <= uint.MaxValue) { goto Label_011D; } Label_01B0: if (((uint) num3) >= 0) { goto Label_00C6; } Label_01C2: if (0xff == 0) { goto Label_017A; } num3 = 0; if ((((uint) index) | 1) != 0) { goto Label_00FA; } goto Label_00C6; Label_020D: helper.WriteProperty("biasActivation", flat.BiasActivation); helper.AddSubSection("ACTIVATION"); activationFunctions = flat.ActivationFunctions; goto Label_01C2; Label_02A1: helper.WriteProperty("layerContextCount", flat.LayerContextCount); helper.WriteProperty("layerIndex", flat.LayerIndex); if ((((uint) index) + ((uint) num)) < 0) { goto Label_0117; } helper.WriteProperty("output", flat.LayerOutput); helper.WriteProperty("outputCount", flat.OutputCount); helper.WriteProperty("weightIndex", flat.WeightIndex); if ((((uint) num) - ((uint) num5)) < 0) { goto Label_03F8; } helper.WriteProperty("weights", flat.Weights); goto Label_020D; Label_02E5: helper.WriteProperty("inputCount", flat.InputCount); helper.WriteProperty("layerCounts", flat.LayerCounts); if ((((uint) num4) - ((uint) index)) < 0) { goto Label_0161; } helper.WriteProperty("layerFeedCounts", flat.LayerFeedCounts); if (0x7fffffff != 0) { goto Label_02A1; } Label_0378: helper.WriteProperty("beginTraining", flat.BeginTraining); helper.WriteProperty("connectionLimit", flat.ConnectionLimit); helper.WriteProperty("contextTargetOffset", flat.ContextTargetOffset); helper.WriteProperty("contextTargetSize", flat.ContextTargetSize); Label_03BC: helper.WriteProperty("endTraining", flat.EndTraining); helper.WriteProperty("hasContext", flat.HasContext); if ((((uint) num5) | 3) == 0) { goto Label_006E; } goto Label_02E5; Label_03F8: helper.AddProperties(network.Properties); helper.AddSubSection("NETWORK"); goto Label_0378; }
/// <inheritdoc/> public void Save(Stream os, Object obj) { var xout = new EncogWriteHelper(os); var boltz = (BoltzmannMachine) obj; xout.AddSection("BOLTZMANN"); xout.AddSubSection("PARAMS"); xout.AddProperties(boltz.Properties); xout.AddSubSection("NETWORK"); xout.WriteProperty(PersistConst.Weights, boltz.Weights); xout.WriteProperty(PersistConst.Output, boltz.CurrentState.Data); xout.WriteProperty(PersistConst.NeuronCount, boltz.NeuronCount); xout.WriteProperty(PersistConst.Thresholds, boltz.Threshold); xout.WriteProperty(BoltzmannMachine.ParamAnnealCycles, boltz.AnnealCycles); xout.WriteProperty(BoltzmannMachine.ParamRunCycles, boltz.RunCycles); xout.WriteProperty(PersistConst.Temperature, boltz.Temperature); xout.Flush(); }
public void Save(Stream os, object obj) { HopfieldNetwork network; EncogWriteHelper helper = new EncogWriteHelper(os); goto Label_00A2; Label_0028: helper.WriteProperty("neurons", network.NeuronCount); helper.Flush(); if (4 != 0) { return; } if (4 != 0) { goto Label_00A2; } goto Label_0064; Label_004C: helper.WriteProperty("output", network.CurrentState.Data); goto Label_0028; Label_0064: helper.AddSection("HOPFIELD"); helper.AddSubSection("PARAMS"); if (2 == 0) { goto Label_004C; } helper.AddProperties(network.Properties); helper.AddSubSection("NETWORK"); if (0 == 0) { helper.WriteProperty("weights", network.Weights); goto Label_004C; } goto Label_0028; Label_00A2: network = (HopfieldNetwork) obj; goto Label_0064; }
public void Save(Stream os, object obj) { EncogWriteHelper helper = new EncogWriteHelper(os); BAMNetwork network = (BAMNetwork) obj; helper.AddSection("BAM"); if (0 == 0) { helper.AddSubSection("PARAMS"); helper.AddProperties(network.Properties); if (0 == 0) { helper.AddSubSection("NETWORK"); helper.WriteProperty("f1Count", network.F1Count); helper.WriteProperty("f2Count", network.F2Count); helper.WriteProperty("weightsF1F2", network.WeightsF1ToF2); helper.WriteProperty("weightsF2F1", network.WeightsF2ToF1); helper.Flush(); } } }
/// <inheritdoc/> public void Save(Stream os, Object obj) { var xout = new EncogWriteHelper(os); var art1 = (ART1) obj; xout.AddSection("ART1"); xout.AddSubSection("PARAMS"); xout.AddProperties(art1.Properties); xout.AddSubSection("NETWORK"); xout.WriteProperty(BasicART.PropertyA1, art1.A1); xout.WriteProperty(BasicART.PropertyB1, art1.B1); xout.WriteProperty(BasicART.PropertyC1, art1.C1); xout.WriteProperty(BasicART.PropertyD1, art1.D1); xout.WriteProperty(PersistConst.PropertyF1Count, art1.F1Count); xout.WriteProperty(PersistConst.PropertyF2Count, art1.F2Count); xout.WriteProperty(BasicART.PropertyNoWinner, art1.NoWinner); xout.WriteProperty(BasicART.PropertyL, art1.L); xout.WriteProperty(BasicART.PropertyVigilance, art1.Vigilance); xout.WriteProperty(PersistConst.PropertyWeightsF1F2, art1.WeightsF1ToF2); xout.WriteProperty(PersistConst.PropertyWeightsF2F1, art1.WeightsF2ToF1); xout.Flush(); }
/// <summary> /// /// </summary> /// public void Save(Stream os, Object obj) { var xout = new EncogWriteHelper(os); var pnn = (BasicPNN) obj; xout.AddSection("PNN"); xout.AddSubSection("PARAMS"); xout.AddProperties(pnn.Properties); xout.AddSubSection("NETWORK"); xout.WriteProperty(PersistConst.Error, pnn.Error); xout.WriteProperty(PersistConst.InputCount, pnn.InputCount); xout.WriteProperty(PersistConst.Kernel, KernelToString(pnn.Kernel)); xout.WriteProperty(PersistConst.OutputCount, pnn.OutputCount); xout.WriteProperty(PropertyOutputMode, OutputModeToString(pnn.OutputMode)); xout.WriteProperty(PersistConst.Sigma, pnn.Sigma); xout.AddSubSection("SAMPLES"); if (pnn.Samples != null) { foreach (IMLDataPair pair in pnn.Samples) { for (int i = 0; i < pair.Input.Count; i++) { xout.AddColumn(pair.Input[i]); } for (int i = 0; i < pair.Ideal.Count; i++) { xout.AddColumn(pair.Ideal[i]); } xout.WriteLine(); } } xout.Flush(); }
/// <summary> /// Save the object. /// </summary> /// <param name="os">The output stream.</param> /// <param name="obj">The object to save.</param> public virtual void Save(Stream os, Object obj) { var xout = new EncogWriteHelper(os); var neat = (NEATNetwork) obj; xout.AddSection("NEAT"); xout.AddSubSection("PARAMS"); xout.AddProperties(neat.Properties); xout.AddSubSection("NETWORK"); xout.WriteProperty(PersistConst.InputCount, neat.InputCount); xout.WriteProperty(PersistConst.OutputCount, neat.OutputCount); xout.WriteProperty(PersistConst.ActivationFunction, neat.ActivationFunction); xout.WriteProperty(NEATPopulation.PropertyOutputActivation, neat.OutputActivationFunction); xout.WriteProperty(PersistConst.Depth, neat.NetworkDepth); xout.WriteProperty(PersistConst.Snapshot, neat.Snapshot); xout.AddSubSection("NEURONS"); foreach (NEATNeuron neatNeuron in neat.Neurons) { xout.AddColumn((int)neatNeuron.NeuronID); xout.AddColumn(PersistNEATPopulation.NeuronTypeToString(neatNeuron.NeuronType)); xout.AddColumn(neatNeuron.ActivationResponse); xout.AddColumn(neatNeuron.SplitX); xout.AddColumn(neatNeuron.SplitY); xout.WriteLine(); } xout.AddSubSection("LINKS"); foreach (NEATNeuron neatNeuron in neat.Neurons) { foreach (NEATLink link in neatNeuron.OutputboundLinks) { WriteLink(xout, link); } } xout.Flush(); }
public virtual void Save(Stream os, object obj) { EncogWriteHelper xout = new EncogWriteHelper(os); NEATNetwork network = (NEATNetwork) obj; xout.AddSection("NEAT"); xout.AddSubSection("PARAMS"); xout.AddProperties(network.Properties); xout.AddSubSection("NETWORK"); if (8 != 0) { } xout.WriteProperty("inputCount", network.InputCount); xout.WriteProperty("outputCount", network.OutputCount); xout.WriteProperty("activationFunction", network.ActivationFunction); xout.WriteProperty("outAct", network.OutputActivationFunction); xout.WriteProperty("depth", network.NetworkDepth); Label_0087: xout.WriteProperty("snapshot", network.Snapshot); xout.AddSubSection("NEURONS"); using (IEnumerator<NEATNeuron> enumerator = network.Neurons.GetEnumerator()) { NEATNeuron current; goto Label_00E3; Label_00B2: if (8 == 0) { goto Label_00F6; } xout.AddColumn(current.ActivationResponse); xout.AddColumn(current.SplitX); xout.AddColumn(current.SplitY); xout.WriteLine(); Label_00E3: if (!enumerator.MoveNext()) { goto Label_0124; } current = enumerator.Current; Label_00F6: xout.AddColumn((int) current.NeuronID); xout.AddColumn(PersistNEATPopulation.NeuronTypeToString(current.NeuronType)); goto Label_00B2; } Label_0124: xout.AddSubSection("LINKS"); foreach (NEATNeuron neuron2 in network.Neurons) { foreach (NEATLink link in neuron2.OutputboundLinks) { WriteLink(xout, link); } } xout.Flush(); if (-1 != 0) { return; } goto Label_0087; }
/** * {@inheritDoc} */ public void Save(Stream os, Object obj) { var writer = new EncogWriteHelper(os); var som = (SOMNetwork) obj; writer.AddSection("SOM"); writer.AddSubSection("PARAMS"); writer.AddProperties(som.Properties); writer.AddSubSection("NETWORK"); writer.WriteProperty(PersistConst.Weights, som.Weights); writer.WriteProperty(PersistConst.InputCount, som.InputCount); writer.WriteProperty(PersistConst.OutputCount, som.OutputCount); writer.Flush(); }
public void Save(Stream os, object obj) { CPNNetwork network; EncogWriteHelper helper = new EncogWriteHelper(os); if (0 == 0) { network = (CPNNetwork) obj; goto Label_00A8; } Label_000D: helper.WriteProperty("inputToInstar", network.WeightsInputToInstar); helper.WriteProperty("instarToInput", network.WeightsInstarToOutstar); helper.WriteProperty("winnerCount", network.WinnerCount); if (-1 != 0) { helper.Flush(); return; } Label_0052: helper.AddProperties(network.Properties); if (0 == 0) { helper.AddSubSection("NETWORK"); helper.WriteProperty("inputCount", network.InputCount); helper.WriteProperty("instar", network.InstarCount); helper.WriteProperty("outputCount", network.OutputCount); goto Label_00C5; } Label_00A8: helper.AddSection("CPN"); helper.AddSubSection("PARAMS"); if (15 != 0) { goto Label_0052; } Label_00C5: if (0 == 0) { goto Label_000D; } }
public void Save(Stream os, object obj) { EncogWriteHelper helper = new EncogWriteHelper(os); BoltzmannMachine machine = (BoltzmannMachine) obj; helper.AddSection("BOLTZMANN"); Label_00C6: helper.AddSubSection("PARAMS"); Label_00D1: helper.AddProperties(machine.Properties); if (0 != 0) { return; } Label_0094: helper.AddSubSection("NETWORK"); helper.WriteProperty("weights", machine.Weights); helper.WriteProperty("output", machine.CurrentState.Data); if (0 == 0) { helper.WriteProperty("neurons", machine.NeuronCount); helper.WriteProperty("thresholds", machine.Threshold); helper.WriteProperty("annealCycles", machine.AnnealCycles); helper.WriteProperty("runCycles", machine.RunCycles); helper.WriteProperty("temperature", machine.Temperature); helper.Flush(); if (0 != 0) { goto Label_00D1; } if (0 == 0) { return; } goto Label_0094; } goto Label_00C6; }
/// <inheritdoc/> public void Save(Stream os, Object obj) { var xout = new EncogWriteHelper(os); var svm2 = (SupportVectorMachine) obj; xout.AddSection("SVM"); xout.AddSubSection("PARAMS"); xout.AddProperties(svm2.Properties); xout.AddSubSection("SVM-PARAM"); xout.WriteProperty(PersistConst.InputCount, svm2.InputCount); xout.WriteProperty(ParamC, svm2.Params.C); xout.WriteProperty(ParamCacheSize, svm2.Params.cache_size); xout.WriteProperty(ParamCoef0, svm2.Params.coef0); xout.WriteProperty(ParamDegree, svm2.Params.degree); xout.WriteProperty(ParamEps, svm2.Params.eps); xout.WriteProperty(ParamGamma, svm2.Params.gamma); xout.WriteProperty(ParamKernelType, svm2.Params.kernel_type); xout.WriteProperty(ParamNumWeight, svm2.Params.nr_weight); xout.WriteProperty(ParamNu, svm2.Params.nu); xout.WriteProperty(ParamP, svm2.Params.p); xout.WriteProperty(ParamProbability, svm2.Params.probability); xout.WriteProperty(ParamShrinking, svm2.Params.shrinking); /* xout.WriteProperty(PersistSVM.PARAM_START_ITERATIONS, svm2.Params.statIterations); */ xout.WriteProperty(ParamSVMType, svm2.Params.svm_type); xout.WriteProperty(ParamWeight, svm2.Params.weight); xout.WriteProperty(ParamWeightLabel, svm2.Params.weight_label); if (svm2.Model != null) { xout.AddSubSection("SVM-MODEL"); try { var ba = new MemoryStream(); var w = new StreamWriter(ba); svm.svm_save_model(w, svm2.Model); var enc = new ASCIIEncoding(); xout.Write(enc.GetString(ba.ToArray())); w.Close(); ba.Close(); } catch (IOException ex) { throw new PersistError(ex); } } xout.Flush(); }
public void Save(Stream os, object obj) { BasicPNN cpnn; int num; int num2; EncogWriteHelper helper = new EncogWriteHelper(os); goto Label_01F0; Label_0017: using (IEnumerator<IMLDataPair> enumerator = cpnn.Samples.GetEnumerator()) { IMLDataPair pair; goto Label_0054; Label_0026: helper.AddColumn(pair.Ideal[num2]); num2++; Label_003F: if (num2 < pair.Ideal.Count) { goto Label_0026; } helper.WriteLine(); Label_0054: if (enumerator.MoveNext()) { goto Label_00F0; } if ((((uint) num) - ((uint) num2)) > uint.MaxValue) { goto Label_00DD; } if ((((uint) num2) + ((uint) num)) >= 0) { goto Label_010F; } if ((((uint) num2) - ((uint) num)) >= 0) { goto Label_00F0; } if ((((uint) num2) + ((uint) num2)) > uint.MaxValue) { goto Label_010F; } Label_00C7: helper.AddColumn(pair.Input[num]); num++; Label_00DD: if (num < pair.Input.Count) { goto Label_00C7; } num2 = 0; goto Label_003F; Label_00F0: pair = enumerator.Current; num = 0; goto Label_00DD; } Label_010F: helper.Flush(); return; Label_01F0: cpnn = (BasicPNN) obj; helper.AddSection("PNN"); helper.AddSubSection("PARAMS"); helper.AddProperties(cpnn.Properties); helper.AddSubSection("NETWORK"); helper.WriteProperty("error", cpnn.Error); helper.WriteProperty("inputCount", cpnn.InputCount); helper.WriteProperty("kernel", KernelToString(cpnn.Kernel)); if ((((uint) num) & 0) != 0) { goto Label_0017; } helper.WriteProperty("outputCount", cpnn.OutputCount); helper.WriteProperty("outputMode", OutputModeToString(cpnn.OutputMode)); if ((((uint) num2) | 1) == 0) { goto Label_0017; } helper.WriteProperty("sigma", cpnn.Sigma); if (0 == 0) { helper.AddSubSection("SAMPLES"); goto Label_0017; } goto Label_01F0; }