/// <inheritdoc/>
public Object Read(Stream mask0)
{
var result = new TrainingContinuation();
var ins0 = new EncogReadHelper(mask0);
EncogFileSection section;
while ((section = ins0.ReadNextSection()) != null)
{
if (section.SectionName.Equals("CONT")
&& section.SubSectionName.Equals("PARAMS"))
{
IDictionary<String, String> paras = section.ParseParams();
foreach (String key in paras.Keys)
{
if (key.Equals("type", StringComparison.InvariantCultureIgnoreCase))
{
result.TrainingType = paras[key];
}
else
{
double[] list = EncogFileSection
.ParseDoubleArray(paras, key);
result.Put(key, list);
}
}
}
}
return result;
}
/**
* {@inheritDoc}
*/
public Object Read(Stream istream)
{
var result = new SOMNetwork();
var reader = new EncogReadHelper(istream);
EncogFileSection section;
while ((section = reader.ReadNextSection()) != null)
{
if (section.SectionName.Equals("SOM")
&& section.SubSectionName.Equals("PARAMS"))
{
IDictionary<String, String> p = section.ParseParams();
EngineArray.PutAll(p, result.Properties);
}
if (section.SectionName.Equals("SOM")
&& section.SubSectionName.Equals("NETWORK"))
{
IDictionary<String, String> p = section.ParseParams();
result.Weights = EncogFileSection.ParseMatrix(p,
PersistConst.Weights)
;
}
}
return result;
}
/// <summary>
/// Read a an object.
/// </summary>
public Object Read(Stream mask0)
{
var result = new HopfieldNetwork();
var ins0 = new EncogReadHelper(mask0);
EncogFileSection section;
while ((section = ins0.ReadNextSection()) != null)
{
if (section.SectionName.Equals("HOPFIELD")
&& section.SubSectionName.Equals("PARAMS"))
{
IDictionary<String, String> paras = section.ParseParams();
EngineArray.PutAll(paras, result.Properties);
}
if (section.SectionName.Equals("HOPFIELD")
&& section.SubSectionName.Equals("NETWORK"))
{
IDictionary<String, String> p = section.ParseParams();
result.Weights = NumberList.FromList(CSVFormat.EgFormat,
(p[PersistConst.Weights]));
result.SetCurrentState(NumberList.FromList(CSVFormat.EgFormat,
(p[PersistConst.Output])));
result.NeuronCount = EncogFileSection.ParseInt(p,
PersistConst.NeuronCount);
}
}
return result;
}
public object Read(Stream mask0)
{
EncogFileSection section;
BAMNetwork network = new BAMNetwork();
EncogReadHelper helper = new EncogReadHelper(mask0);
goto Label_002F;
Label_000B:
if (!section.SectionName.Equals("BAM"))
{
goto Label_002F;
}
Label_001D:
if (section.SubSectionName.Equals("NETWORK"))
{
IDictionary<string, string> paras = section.ParseParams();
network.F1Count = EncogFileSection.ParseInt(paras, "f1Count");
network.F2Count = EncogFileSection.ParseInt(paras, "f2Count");
if (0 != 0)
{
goto Label_000B;
}
network.WeightsF1ToF2 = EncogFileSection.ParseMatrix(paras, "weightsF1F2");
if (0 != 0)
{
goto Label_00C2;
}
network.WeightsF2ToF1 = EncogFileSection.ParseMatrix(paras, "weightsF2F1");
}
Label_002F:
if ((section = helper.ReadNextSection()) != null)
{
if (!section.SectionName.Equals("BAM"))
{
goto Label_000B;
}
}
else
{
return network;
}
Label_00AB:
if (section.SubSectionName.Equals("PARAMS"))
{
EngineArray.PutAll<string, string>(section.ParseParams(), network.Properties);
}
else
{
goto Label_000B;
}
Label_00C2:
if (0 != 0)
{
goto Label_00AB;
}
if (15 != 0)
{
goto Label_000B;
}
goto Label_001D;
}
/// <inheritdoc/>
public Object Read(Stream mask0)
{
var result = new BAMNetwork();
var ins0 = new EncogReadHelper(mask0);
EncogFileSection section;
while ((section = ins0.ReadNextSection()) != null)
{
if (section.SectionName.Equals("BAM")
&& section.SubSectionName.Equals("PARAMS"))
{
IDictionary<String, String> paras = section.ParseParams();
EngineArray.PutAll(paras, result.Properties);
}
if (section.SectionName.Equals("BAM")
&& section.SubSectionName.Equals("NETWORK"))
{
IDictionary<String, String> p = section.ParseParams();
result.F1Count = EncogFileSection.ParseInt(p,
PersistConst.PropertyF1Count);
result.F2Count = EncogFileSection.ParseInt(p,
PersistConst.PropertyF2Count);
result.WeightsF1ToF2 = EncogFileSection.ParseMatrix(p,PersistConst.PropertyWeightsF1F2);
result.WeightsF2ToF1 = EncogFileSection.ParseMatrix(p,PersistConst.PropertyWeightsF2F1);
}
}
return result;
}
/// <inheritdoc/>
public Object Read(Stream mask0)
{
var result = new ART1();
var ins0 = new EncogReadHelper(mask0);
EncogFileSection section;
while ((section = ins0.ReadNextSection()) != null)
{
if (section.SectionName.Equals("ART1")
&& section.SubSectionName.Equals("PARAMS"))
{
IDictionary<String, String> paras = section.ParseParams();
EngineArray.PutAll(paras, result.Properties);
}
if (section.SectionName.Equals("ART1")
&& section.SubSectionName.Equals("NETWORK"))
{
IDictionary<String, String> p = section.ParseParams();
result.A1 = EncogFileSection.ParseDouble(p,
BasicART.PropertyA1);
result.B1 = EncogFileSection.ParseDouble(p,
BasicART.PropertyB1);
result.C1 = EncogFileSection.ParseDouble(p,
BasicART.PropertyC1);
result.D1 = EncogFileSection.ParseDouble(p,
BasicART.PropertyD1);
result.F1Count = EncogFileSection.ParseInt(p,
PersistConst.PropertyF1Count);
result.F2Count = EncogFileSection.ParseInt(p,
PersistConst.PropertyF2Count);
result.NoWinner = EncogFileSection.ParseInt(p,
BasicART.PropertyNoWinner);
result.L = EncogFileSection
.ParseDouble(p, BasicART.PropertyL);
result.Vigilance = EncogFileSection.ParseDouble(p,
BasicART.PropertyVigilance);
result.WeightsF1ToF2 = EncogFileSection.ParseMatrix(p,
PersistConst.PropertyWeightsF1F2);
result.WeightsF2ToF1 = EncogFileSection.ParseMatrix(p,
PersistConst.PropertyWeightsF2F1);
}
}
return result;
}
/// <inheritdoc/>
public Object Read(Stream mask0)
{
IDictionary<String, String> networkParams = null;
var ins0 = new EncogReadHelper(mask0);
EncogFileSection section;
int inputCount = 0;
int instarCount = 0;
int outputCount = 0;
int winnerCount = 0;
Matrix m1 = null;
Matrix m2 = null;
while ((section = ins0.ReadNextSection()) != null)
{
if (section.SectionName.Equals("CPN")
&& section.SubSectionName.Equals("PARAMS"))
{
networkParams = section.ParseParams();
}
if (section.SectionName.Equals("CPN")
&& section.SubSectionName.Equals("NETWORK"))
{
IDictionary<String, String> paras = section.ParseParams();
inputCount = EncogFileSection.ParseInt(paras,
PersistConst.InputCount);
instarCount = EncogFileSection.ParseInt(paras,
PersistConst.Instar);
outputCount = EncogFileSection.ParseInt(paras,
PersistConst.OutputCount);
winnerCount = EncogFileSection.ParseInt(paras,
PropertyWinnerCount);
m1 = EncogFileSection.ParseMatrix(paras,
PropertyInputToInstar);
m2 = EncogFileSection.ParseMatrix(paras,
PropertyInstarToInput);
}
}
var result = new CPNNetwork(inputCount, instarCount, outputCount,
winnerCount);
EngineArray.PutAll(networkParams, result.Properties);
result.WeightsInputToInstar.Set(m1);
result.WeightsInstarToOutstar.Set(m2);
return result;
}
public void Load(Stream stream)
{
EncogReadHelper helper = null;
try
{
EncogFileSection section;
helper = new EncogReadHelper(stream);
while ((section = helper.ReadNextSection()) != null)
{
this.xf9edee23632d6876(section);
}
this._x594135906c55045c.Init();
}
finally
{
if (helper != null)
{
helper.Close();
}
}
}
/// <inheritdoc/>
public Object Read(Stream mask0)
{
var result = new BoltzmannMachine();
var ins0 = new EncogReadHelper(mask0);
EncogFileSection section;
while ((section = ins0.ReadNextSection()) != null)
{
if (section.SectionName.Equals("BOLTZMANN")
&& section.SubSectionName.Equals("PARAMS"))
{
IDictionary<String, String> paras = section.ParseParams();
EngineArray.PutAll(paras, result.Properties);
}
if (section.SectionName.Equals("BOLTZMANN")
&& section.SubSectionName.Equals("NETWORK"))
{
IDictionary<String, String> p = section.ParseParams();
result.Weights = NumberList.FromList(CSVFormat.EgFormat,
(p[PersistConst.Weights]));
result.SetCurrentState(NumberList.FromList(CSVFormat.EgFormat,
(p[PersistConst.Output])));
result.NeuronCount = EncogFileSection.ParseInt(p,
PersistConst.NeuronCount);
result.Threshold = NumberList.FromList(CSVFormat.EgFormat,
(p[PersistConst.Thresholds]));
result.AnnealCycles = EncogFileSection.ParseInt(p,
BoltzmannMachine.ParamAnnealCycles);
result.RunCycles = EncogFileSection.ParseInt(p,
BoltzmannMachine.ParamRunCycles);
result.Temperature = EncogFileSection.ParseDouble(p,
PersistConst.Temperature);
}
}
return result;
}
public object Read(Stream mask0)
{
FlatNetwork network2;
EncogReadHelper helper;
EncogFileSection section;
IDictionary<string, string> dictionary2;
int num;
int num2;
BasicNetwork network = new BasicNetwork();
goto Label_03B8;
Label_000B:
if ((section = helper.ReadNextSection()) != null)
{
goto Label_036A;
}
network.Structure.Flat = network2;
if ((((uint) num) - ((uint) num2)) <= uint.MaxValue)
{
if (8 != 0)
{
return network;
}
goto Label_03B8;
}
Label_003F:
num = 0;
network2.ActivationFunctions = new IActivationFunction[network2.LayerCounts.Length];
using (IEnumerator<string> enumerator = section.Lines.GetEnumerator())
{
string str;
IActivationFunction function;
IList<string> list;
Label_0064:
if (enumerator.MoveNext())
{
goto Label_00E2;
}
goto Label_000B;
Label_0072:
network2.ActivationFunctions[num++] = function;
if (0 == 0)
{
goto Label_00D6;
}
Label_0087:
num2 = 0;
while (num2 < function.ParamNames.Length)
{
function.Params[num2] = CSVFormat.EgFormat.Parse(list[num2 + 1]);
num2++;
}
if ((((uint) num) + ((uint) num2)) <= uint.MaxValue)
{
goto Label_0072;
}
Label_00D6:
if (4 != 0)
{
goto Label_0064;
}
goto Label_000B;
Label_00E2:
str = enumerator.Current;
list = EncogFileSection.SplitColumns(str);
string name = "Encog.Engine.Network.Activation." + list[0];
try
{
function = (IActivationFunction) ReflectionUtil.LoadObject(name);
goto Label_0087;
}
catch (TypeLoadException exception)
{
throw new PersistError(exception);
}
catch (TargetException exception2)
{
throw new PersistError(exception2);
}
catch (MemberAccessException exception3)
{
throw new PersistError(exception3);
}
}
goto Label_000B;
Label_0182:
if (!section.SectionName.Equals("BASIC"))
{
goto Label_01A9;
}
Label_0194:
if (section.SubSectionName.Equals("NETWORK"))
{
dictionary2 = section.ParseParams();
network2.BeginTraining = EncogFileSection.ParseInt(dictionary2, "beginTraining");
network2.ConnectionLimit = EncogFileSection.ParseDouble(dictionary2, "connectionLimit");
goto Label_032A;
}
Label_01A9:
if (section.SectionName.Equals("BASIC") && section.SubSectionName.Equals("ACTIVATION"))
{
goto Label_003F;
}
goto Label_000B;
Label_032A:
network2.ContextTargetOffset = EncogFileSection.ParseIntArray(dictionary2, "contextTargetOffset");
network2.ContextTargetSize = EncogFileSection.ParseIntArray(dictionary2, "contextTargetSize");
network2.EndTraining = EncogFileSection.ParseInt(dictionary2, "endTraining");
network2.HasContext = EncogFileSection.ParseBoolean(dictionary2, "hasContext");
network2.InputCount = EncogFileSection.ParseInt(dictionary2, "inputCount");
if ((((uint) num2) - ((uint) num2)) <= uint.MaxValue)
{
if ((((uint) num) + ((uint) num)) > uint.MaxValue)
{
return network;
}
network2.LayerCounts = EncogFileSection.ParseIntArray(dictionary2, "layerCounts");
do
{
network2.LayerFeedCounts = EncogFileSection.ParseIntArray(dictionary2, "layerFeedCounts");
network2.LayerContextCount = EncogFileSection.ParseIntArray(dictionary2, "layerContextCount");
network2.LayerIndex = EncogFileSection.ParseIntArray(dictionary2, "layerIndex");
network2.LayerOutput = EncogFileSection.ParseDoubleArray(dictionary2, "output");
}
while ((((uint) num) + ((uint) num)) < 0);
network2.LayerSums = new double[network2.LayerOutput.Length];
network2.OutputCount = EncogFileSection.ParseInt(dictionary2, "outputCount");
network2.WeightIndex = EncogFileSection.ParseIntArray(dictionary2, "weightIndex");
do
{
network2.Weights = EncogFileSection.ParseDoubleArray(dictionary2, "weights");
}
while (0 != 0);
network2.BiasActivation = EncogFileSection.ParseDoubleArray(dictionary2, "biasActivation");
goto Label_000B;
}
Label_036A:
if (section.SectionName.Equals("BASIC"))
{
if (section.SubSectionName.Equals("PARAMS"))
{
EngineArray.PutAll<string, string>(section.ParseParams(), network.Properties);
}
goto Label_0182;
}
if (0 == 0)
{
goto Label_0182;
}
if ((((uint) num2) + ((uint) num2)) < 0)
{
goto Label_032A;
}
goto Label_0194;
Label_03B8:
network2 = new FlatNetwork();
helper = new EncogReadHelper(mask0);
goto Label_000B;
}
/// <summary>
/// Read an object.
/// </summary>
public Object Read(Stream mask0)
{
var ins0 = new EncogReadHelper(mask0);
EncogFileSection section;
var samples = new BasicMLDataSet();
IDictionary<String, String> networkParams = null;
PNNKernelType kernel = default(PNNKernelType) /* was: null */;
PNNOutputMode outmodel = default(PNNOutputMode) /* was: null */;
int inputCount = 0;
int outputCount = 0;
double error = 0;
double[] sigma = null;
while ((section = ins0.ReadNextSection()) != null)
{
if (section.SectionName.Equals("PNN")
&& section.SubSectionName.Equals("PARAMS"))
{
networkParams = section.ParseParams();
}
if (section.SectionName.Equals("PNN")
&& section.SubSectionName.Equals("NETWORK"))
{
IDictionary<String, String> paras = section.ParseParams();
inputCount = EncogFileSection.ParseInt(paras,
PersistConst.InputCount);
outputCount = EncogFileSection.ParseInt(paras,
PersistConst.OutputCount);
kernel = StringToKernel(paras[PersistConst.Kernel]);
outmodel = StringToOutputMode(paras[PropertyOutputMode]);
error = EncogFileSection
.ParseDouble(paras, PersistConst.Error);
sigma = section.ParseDoubleArray(paras, PersistConst.Sigma);
}
if (section.SectionName.Equals("PNN")
&& section.SubSectionName.Equals("SAMPLES"))
{
foreach (String line in section.Lines)
{
IList<String> cols = EncogFileSection
.SplitColumns(line);
int index = 0;
var inputData = new BasicMLData(inputCount);
for (int i = 0; i < inputCount; i++)
{
inputData[i] =
CSVFormat.EgFormat.Parse(cols[index++]);
}
var idealData = new BasicMLData(inputCount);
idealData[0] = CSVFormat.EgFormat.Parse(cols[index++]);
IMLDataPair pair = new BasicMLDataPair(inputData,
idealData);
samples.Add(pair);
}
}
}
var result = new BasicPNN(kernel, outmodel, inputCount,
outputCount);
if (networkParams != null)
{
EngineArray.PutAll(networkParams, result.Properties);
}
result.Samples = samples;
result.Error = error;
if (sigma != null)
{
EngineArray.ArrayCopy(sigma, result.Sigma);
}
return result;
}
/// <summary>
/// Read an object.
/// </summary>
///
public Object Read(Stream mask0)
{
var result = new BasicNetwork();
var flat = new FlatNetwork();
var ins0 = new EncogReadHelper(mask0);
EncogFileSection section;
while ((section = ins0.ReadNextSection()) != null)
{
if (section.SectionName.Equals("BASIC")
&& section.SubSectionName.Equals("PARAMS"))
{
IDictionary<String, String> paras = section.ParseParams();
EngineArray.PutAll(paras, result.Properties);
}
if (section.SectionName.Equals("BASIC")
&& section.SubSectionName.Equals("NETWORK"))
{
IDictionary<String, String> p = section.ParseParams();
flat.BeginTraining = EncogFileSection.ParseInt(p,
BasicNetwork.TagBeginTraining);
flat.ConnectionLimit = EncogFileSection.ParseDouble(p,
BasicNetwork.TagConnectionLimit);
flat.ContextTargetOffset = EncogFileSection.ParseIntArray(
p, BasicNetwork.TagContextTargetOffset);
flat.ContextTargetSize = EncogFileSection.ParseIntArray(
p, BasicNetwork.TagContextTargetSize);
flat.EndTraining = EncogFileSection.ParseInt(p,
BasicNetwork.TagEndTraining);
flat.HasContext = EncogFileSection.ParseBoolean(p,
BasicNetwork.TagHasContext);
flat.InputCount = EncogFileSection.ParseInt(p,
PersistConst.InputCount);
flat.LayerCounts = EncogFileSection.ParseIntArray(p,
BasicNetwork.TagLayerCounts);
flat.LayerFeedCounts = EncogFileSection.ParseIntArray(p,
BasicNetwork.TagLayerFeedCounts);
flat.LayerContextCount = EncogFileSection.ParseIntArray(
p, BasicNetwork.TagLayerContextCount);
flat.LayerIndex = EncogFileSection.ParseIntArray(p,
BasicNetwork.TagLayerIndex);
flat.LayerOutput = section.ParseDoubleArray(p,PersistConst.Output);
flat.LayerSums = new double[flat.LayerOutput.Length];
flat.OutputCount = EncogFileSection.ParseInt(p,
PersistConst.OutputCount);
flat.WeightIndex = EncogFileSection.ParseIntArray(p,
BasicNetwork.TagWeightIndex);
flat.Weights = section.ParseDoubleArray(p, PersistConst.Weights);
flat.BiasActivation = section.ParseDoubleArray(p, BasicNetwork.TagBiasActivation);
}
else if (section.SectionName.Equals("BASIC")
&& section.SubSectionName.Equals("ACTIVATION"))
{
int index = 0;
flat.ActivationFunctions = new IActivationFunction[flat.LayerCounts.Length];
foreach (String line in section.Lines)
{
IActivationFunction af;
IList<String> cols = EncogFileSection
.SplitColumns(line);
String name = ReflectionUtil.AfPath
+ cols[0];
try
{
af = (IActivationFunction) ReflectionUtil.LoadObject(name);
}
catch (TypeLoadException e)
{
throw new PersistError(e);
}
catch (TargetException e)
{
throw new PersistError(e);
}
catch (MemberAccessException e)
{
throw new PersistError(e);
}
for (int i = 0; i < af.ParamNames.Length; i++)
{
af.Params[i] =
CSVFormat.EgFormat.Parse(cols[i + 1]);
}
flat.ActivationFunctions[index++] = af;
}
}
}
result.Structure.Flat = flat;
return result;
}
/// <inheritdoc/>
public Object Read(Stream istream)
{
long nextInnovationId = 0;
long nextGeneId = 0;
var result = new NEATPopulation();
var innovationList = new NEATInnovationList {Population = result};
result.Innovations = innovationList;
var reader = new EncogReadHelper(istream);
EncogFileSection section;
while ((section = reader.ReadNextSection()) != null)
{
if (section.SectionName.Equals("NEAT-POPULATION")
&& section.SubSectionName.Equals("INNOVATIONS"))
{
foreach (String line in section.Lines)
{
IList<String> cols = EncogFileSection
.SplitColumns(line);
var innovation = new NEATInnovation();
var innovationId = int.Parse(cols[1]);
innovation.InnovationId = innovationId;
innovation.NeuronId = int.Parse(cols[2]);
result.Innovations.Innovations[cols[0]] = innovation;
nextInnovationId = Math.Max(nextInnovationId, innovationId + 1);
}
}
else if (section.SectionName.Equals("NEAT-POPULATION")
&& section.SubSectionName.Equals("SPECIES"))
{
NEATGenome lastGenome = null;
BasicSpecies lastSpecies = null;
foreach (String line in section.Lines)
{
IList<String> cols = EncogFileSection.SplitColumns(line);
if (String.Compare(cols[0], "s", StringComparison.OrdinalIgnoreCase) == 0)
{
lastSpecies = new BasicSpecies
{
Population = result,
Age = int.Parse(cols[1]),
BestScore = CSVFormat.EgFormat.Parse(cols[2]),
GensNoImprovement = int.Parse(cols[3])
};
result.Species.Add(lastSpecies);
}
else if (String.Compare(cols[0], "g", StringComparison.OrdinalIgnoreCase) == 0)
{
bool isLeader = lastGenome == null;
lastGenome = new NEATGenome
{
InputCount = result.InputCount,
OutputCount = result.OutputCount,
Species = lastSpecies,
AdjustedScore = CSVFormat.EgFormat.Parse(cols[1]),
Score = CSVFormat.EgFormat.Parse(cols[2]),
BirthGeneration = int.Parse(cols[3])
};
lastSpecies.Add(lastGenome);
if (isLeader)
{
lastSpecies.Leader = lastGenome;
}
}
else if (String.Compare(cols[0], "n", StringComparison.OrdinalIgnoreCase) == 0)
{
var neuronGene = new NEATNeuronGene();
int geneId = int.Parse(cols[1]);
neuronGene.Id = geneId;
IActivationFunction af = EncogFileSection.ParseActivationFunction(cols[2]);
neuronGene.ActivationFunction = af;
neuronGene.NeuronType = PersistNEATPopulation.StringToNeuronType(cols[3]);
neuronGene.InnovationId = int.Parse(cols[4]);
lastGenome.NeuronsChromosome.Add(neuronGene);
nextGeneId = Math.Max(geneId + 1, nextGeneId);
}
else if (String.Compare(cols[0], "l", StringComparison.OrdinalIgnoreCase) == 0)
{
var linkGene = new NEATLinkGene
{
Id = int.Parse(cols[1]),
Enabled = (int.Parse(cols[2]) > 0),
FromNeuronId = int.Parse(cols[3]),
ToNeuronId = int.Parse(cols[4]),
Weight = CSVFormat.EgFormat.Parse(cols[5]),
InnovationId = int.Parse(cols[6])
};
lastGenome.LinksChromosome.Add(linkGene);
}
}
}
else if (section.SectionName.Equals("NEAT-POPULATION")
&& section.SubSectionName.Equals("CONFIG"))
{
IDictionary<string, string> prm = section.ParseParams();
string afStr = prm[NEATPopulation.PropertyNEATActivation];
if (String.Compare(afStr, TypeCppn, StringComparison.OrdinalIgnoreCase) == 0)
{
HyperNEATGenome.BuildCPPNActivationFunctions(result.ActivationFunctions);
}
else
{
result.NEATActivationFunction = EncogFileSection.ParseActivationFunction(prm,
NEATPopulation.PropertyNEATActivation);
}
result.ActivationCycles = EncogFileSection.ParseInt(prm,
PersistConst.ActivationCycles);
result.InputCount = EncogFileSection.ParseInt(prm,
PersistConst.InputCount);
result.OutputCount = EncogFileSection.ParseInt(prm,
PersistConst.OutputCount);
result.PopulationSize = EncogFileSection.ParseInt(prm,
NEATPopulation.PropertyPopulationSize);
result.SurvivalRate = EncogFileSection.ParseDouble(prm,
NEATPopulation.PropertySurvivalRate);
result.ActivationCycles = EncogFileSection.ParseInt(prm,
NEATPopulation.PropertyCycles);
}
}
// set factories
if (result.IsHyperNEAT)
{
result.GenomeFactory = new FactorHyperNEATGenome();
result.CODEC = new HyperNEATCODEC();
}
else
{
result.GenomeFactory = new FactorNEATGenome();
result.CODEC = new NEATCODEC();
}
// set the next ID's
result.InnovationIDGenerate.CurrentID = nextInnovationId;
result.GeneIdGenerate.CurrentID = nextGeneId;
// find first genome, which should be the best genome
if (result.Species.Count > 0)
{
ISpecies species = result.Species[0];
if (species.Members.Count > 0)
{
result.BestGenome = species.Members[0];
}
}
return result;
}
public virtual object Read(Stream mask0)
{
IDictionary<ISpecies, int> dictionary2;
IDictionary<int, IGenome> dictionary3;
EncogFileSection section;
IDictionary<string, string> dictionary4;
int num;
int num2;
NEATPopulation population = new NEATPopulation();
NEATInnovationList list = new NEATInnovationList {
Population = population
};
population.Innovations = list;
EncogReadHelper helper = new EncogReadHelper(mask0);
IDictionary<int, ISpecies> dictionary = new Dictionary<int, ISpecies>();
goto Label_0BD6;
Label_0023:
if ((section = helper.ReadNextSection()) != null)
{
if (!section.SectionName.Equals("NEAT-POPULATION"))
{
goto Label_085C;
}
if (section.SubSectionName.Equals("INNOVATIONS"))
{
using (IEnumerator<string> enumerator = section.Lines.GetEnumerator())
{
string str;
IList<string> list2;
NEATInnovation innovation;
NEATInnovation innovation2;
goto Label_0A6C;
Label_0A43:
innovation = innovation2;
if ((((uint) num2) - ((uint) num)) <= uint.MaxValue)
{
}
population.Innovations.Add(innovation);
Label_0A6C:
if (enumerator.MoveNext())
{
goto Label_0B54;
}
goto Label_0AD7;
Label_0A7A:
innovation2.SplitY = CSVFormat.EgFormat.Parse(list2[4]);
innovation2.NeuronID = int.Parse(list2[5]);
innovation2.FromNeuronID = int.Parse(list2[6]);
innovation2.ToNeuronID = int.Parse(list2[7]);
goto Label_0A43;
Label_0AD7:
if ((((uint) num2) - ((uint) num)) >= 0)
{
goto Label_0023;
}
Label_0AEF:
innovation2 = new NEATInnovation();
innovation2.InnovationID = int.Parse(list2[0]);
innovation2.InnovationType = StringToInnovationType(list2[1]);
innovation2.NeuronType = StringToNeuronType(list2[2]);
innovation2.SplitX = CSVFormat.EgFormat.Parse(list2[3]);
if (0 == 0)
{
goto Label_0A7A;
}
goto Label_0023;
Label_0B54:
str = enumerator.Current;
do
{
list2 = EncogFileSection.SplitColumns(str);
}
while (0 != 0);
goto Label_0AEF;
}
}
if (((uint) num) <= uint.MaxValue)
{
goto Label_085C;
}
goto Label_030B;
}
using (IEnumerator<IGenome> enumerator4 = population.Genomes.GetEnumerator())
{
IGenome genome3;
NEATGenome genome4;
ISpecies species3;
Label_0040:
if (enumerator4.MoveNext())
{
goto Label_00D6;
}
goto Label_0102;
Label_0051:
genome4.OutputCount = population.OutputCount;
if ((((uint) num) - ((uint) num2)) >= 0)
{
goto Label_0040;
}
Label_007D:
if (dictionary.ContainsKey(num))
{
goto Label_00BA;
}
Label_0087:
genome4.InputCount = population.InputCount;
goto Label_0051;
Label_0096:
num = (int) genome4.SpeciesID;
if ((((uint) num2) + ((uint) num2)) <= uint.MaxValue)
{
}
goto Label_007D;
Label_00BA:
species3 = dictionary[num];
species3.Members.Add(genome4);
goto Label_0087;
Label_00D6:
genome3 = enumerator4.Current;
genome4 = (NEATGenome) genome3;
goto Label_0096;
}
Label_0102:
using (IEnumerator<ISpecies> enumerator5 = dictionary2.Keys.GetEnumerator())
{
ISpecies current;
goto Label_011F;
Label_0112:
((BasicSpecies) current).Population = population;
Label_011F:
if (enumerator5.MoveNext())
{
current = enumerator5.Current;
num2 = dictionary2[current];
do
{
IGenome genome5 = dictionary3[num2];
current.Leader = genome5;
}
while (-1 == 0);
goto Label_0112;
}
return population;
}
Label_016E:
population.YoungScoreBonus = EncogFileSection.ParseDouble(dictionary4, "youngAgeBonus");
population.GenomeIDGenerate.CurrentID = EncogFileSection.ParseInt(dictionary4, "nextGenomeID");
population.InnovationIDGenerate.CurrentID = EncogFileSection.ParseInt(dictionary4, "nextInnovationID");
population.GeneIDGenerate.CurrentID = EncogFileSection.ParseInt(dictionary4, "nextGeneID");
population.SpeciesIDGenerate.CurrentID = EncogFileSection.ParseInt(dictionary4, "nextSpeciesID");
goto Label_0023;
Label_0201:
population.SurvivalRate = EncogFileSection.ParseDouble(dictionary4, "survivalRate");
if (0 != 0)
{
goto Label_03AA;
}
goto Label_02E9;
Label_0242:
population.OldAgePenalty = EncogFileSection.ParseDouble(dictionary4, "oldAgePenalty");
population.OldAgeThreshold = EncogFileSection.ParseInt(dictionary4, "oldAgeThreshold");
Label_0266:
population.PopulationSize = EncogFileSection.ParseInt(dictionary4, "populationSize");
if (((uint) num2) <= uint.MaxValue)
{
if ((((uint) num2) - ((uint) num2)) >= 0)
{
if ((((uint) num) + ((uint) num2)) > uint.MaxValue)
{
goto Label_0242;
}
goto Label_0201;
}
goto Label_02E9;
}
Label_028A:
population.OutputActivationFunction = EncogFileSection.ParseActivationFunction(dictionary4, "outAct");
if ((((uint) num2) + ((uint) num2)) < 0)
{
goto Label_0BD6;
}
population.Snapshot = EncogFileSection.ParseBoolean(dictionary4, "snapshot");
population.InputCount = EncogFileSection.ParseInt(dictionary4, "inputCount");
population.OutputCount = EncogFileSection.ParseInt(dictionary4, "outputCount");
goto Label_0242;
Label_02E9:
if ((((uint) num2) - ((uint) num)) >= 0)
{
population.YoungBonusAgeThreshhold = EncogFileSection.ParseInt(dictionary4, "youngAgeThreshold");
}
if (0xff != 0)
{
goto Label_016E;
}
Label_030B:
population.NeatActivationFunction = EncogFileSection.ParseActivationFunction(dictionary4, "neatAct");
goto Label_028A;
Label_03AA:
if (!section.SectionName.Equals("NEAT-POPULATION") || !section.SubSectionName.Equals("CONFIG"))
{
goto Label_0023;
}
if ((((uint) num2) + ((uint) num2)) <= uint.MaxValue)
{
if ((((uint) num2) + ((uint) num2)) <= uint.MaxValue)
{
dictionary4 = section.ParseParams();
}
goto Label_030B;
}
Label_0821:
if (section.SectionName.Equals("NEAT-POPULATION"))
{
if (section.SubSectionName.Equals("GENOMES"))
{
NEATGenome genome = null;
using (IEnumerator<string> enumerator3 = section.Lines.GetEnumerator())
{
string str3;
IList<string> list3;
NEATGenome genome2;
NEATNeuronGene gene;
NEATNeuronGene gene2;
NEATLinkGene gene3;
goto Label_0402;
Label_03DA:
genome.Links.Add(gene3);
goto Label_0402;
Label_03EA:
if (list3[0].Equals("l", StringComparison.InvariantCultureIgnoreCase))
{
goto Label_04EA;
}
Label_0402:
if (enumerator3.MoveNext())
{
goto Label_0770;
}
if ((((uint) num2) | 0x80000000) != 0)
{
goto Label_0023;
}
Label_0429:
gene3.Enabled = int.Parse(list3[2]) > 0;
Label_0440:
gene3.Recurrent = int.Parse(list3[3]) > 0;
gene3.FromNeuronID = int.Parse(list3[4]);
gene3.ToNeuronID = int.Parse(list3[5]);
gene3.Weight = CSVFormat.EgFormat.Parse(list3[6]);
gene3.InnovationId = int.Parse(list3[7]);
goto Label_03DA;
Label_04B4:
if ((((uint) num) & 0) != 0)
{
goto Label_03DA;
}
gene3.Id = int.Parse(list3[1]);
goto Label_0429;
Label_04EA:
gene3 = new NEATLinkGene();
goto Label_04B4;
Label_04F6:
gene2.SplitY = CSVFormat.EgFormat.Parse(list3[7]);
Label_050F:
gene = gene2;
genome.Neurons.Add(gene);
if ((((uint) num2) & 0) != 0)
{
goto Label_0782;
}
goto Label_0402;
Label_053D:
gene2.Enabled = int.Parse(list3[3]) > 0;
gene2.InnovationId = int.Parse(list3[4]);
if (0xff == 0)
{
goto Label_050F;
}
gene2.ActivationResponse = CSVFormat.EgFormat.Parse(list3[5]);
gene2.SplitX = CSVFormat.EgFormat.Parse(list3[6]);
goto Label_04F6;
Label_05A7:
gene2.Id = int.Parse(list3[1]);
gene2.NeuronType = StringToNeuronType(list3[2]);
goto Label_053D;
Label_05DA:
if (!list3[0].Equals("n", StringComparison.InvariantCultureIgnoreCase))
{
goto Label_03EA;
}
if (3 == 0)
{
goto Label_0440;
}
gene2 = new NEATNeuronGene();
goto Label_07C8;
Label_0608:
population.Add(genome);
dictionary3[(int) genome.GenomeID] = genome;
if (((uint) num) >= 0)
{
goto Label_0402;
}
goto Label_06B0;
Label_0638:
genome.AmountToSpawn = CSVFormat.EgFormat.Parse(list3[4]);
genome.NetworkDepth = int.Parse(list3[5]);
if ((((uint) num2) | 0x80000000) == 0)
{
goto Label_07AD;
}
if (((uint) num2) < 0)
{
goto Label_0023;
}
genome.Score = CSVFormat.EgFormat.Parse(list3[6]);
goto Label_06F8;
Label_06B0:
genome.GenomeID = int.Parse(list3[1]);
genome.SpeciesID = int.Parse(list3[2]);
genome.AdjustedScore = CSVFormat.EgFormat.Parse(list3[3]);
goto Label_0638;
Label_06F8:
if (3 != 0)
{
goto Label_0608;
}
goto Label_0402;
Label_0704:
genome.Chromosomes.Add(genome.LinksChromosome);
if ((((uint) num2) + ((uint) num2)) >= 0)
{
goto Label_06B0;
}
goto Label_0402;
Label_0737:
if (8 == 0)
{
goto Label_050F;
}
genome = genome2;
genome.Chromosomes.Add(genome.NeuronsChromosome);
if ((((uint) num) - ((uint) num2)) <= uint.MaxValue)
{
goto Label_0704;
}
Label_0770:
str3 = enumerator3.Current;
list3 = EncogFileSection.SplitColumns(str3);
Label_0782:
if (!list3[0].Equals("g", StringComparison.InvariantCultureIgnoreCase))
{
goto Label_05DA;
}
genome2 = new NEATGenome {
NeuronsChromosome = new Chromosome()
};
Label_07AD:
genome2.LinksChromosome = new Chromosome();
goto Label_0737;
Label_07C8:
if ((((uint) num2) - ((uint) num)) <= uint.MaxValue)
{
goto Label_05A7;
}
if (0 == 0)
{
goto Label_04EA;
}
goto Label_04B4;
}
}
if ((((uint) num2) < 0) || ((((uint) num2) - ((uint) num2)) > uint.MaxValue))
{
goto Label_030B;
}
}
goto Label_03AA;
Label_085C:
if (section.SectionName.Equals("NEAT-POPULATION"))
{
if ((((uint) num) | 1) == 0)
{
goto Label_0266;
}
if (section.SubSectionName.Equals("SPECIES"))
{
if ((((uint) num) | 8) == 0)
{
goto Label_0201;
}
using (IEnumerator<string> enumerator2 = section.Lines.GetEnumerator())
{
string str2;
string[] strArray;
BasicSpecies species;
BasicSpecies species2;
goto Label_0913;
Label_08CB:
species = species2;
species.SpawnsRequired = CSVFormat.EgFormat.Parse(strArray[5]);
dictionary2[species] = int.Parse(strArray[6]);
population.Species.Add(species);
dictionary[(int) species.SpeciesID] = species;
Label_0913:
if (enumerator2.MoveNext())
{
goto Label_09D6;
}
goto Label_0023;
Label_0924:
if ((((uint) num2) & 0) != 0)
{
goto Label_0969;
}
if (2 == 0)
{
goto Label_0924;
}
goto Label_09BE;
Label_0941:
species2 = new BasicSpecies();
species2.SpeciesID = int.Parse(strArray[0]);
species2.Age = int.Parse(strArray[1]);
Label_0969:
species2.BestScore = CSVFormat.EgFormat.Parse(strArray[2]);
species2.GensNoImprovement = int.Parse(strArray[3]);
species2.SpawnsRequired = CSVFormat.EgFormat.Parse(strArray[4]);
if ((((uint) num) + ((uint) num2)) >= 0)
{
goto Label_0924;
}
Label_09BE:
if ((((uint) num2) + ((uint) num)) <= uint.MaxValue)
{
goto Label_09FD;
}
Label_09D6:
str2 = enumerator2.Current;
strArray = str2.Split(new char[] { ',' });
goto Label_0941;
Label_09FD:
if ((((uint) num) - ((uint) num)) <= uint.MaxValue)
{
goto Label_08CB;
}
goto Label_0023;
}
}
}
goto Label_0821;
Label_0BD6:
dictionary2 = new Dictionary<ISpecies, int>();
dictionary3 = new Dictionary<int, IGenome>();
goto Label_0023;
}
/// <inheritdoc/>
public Object Read(Stream mask0)
{
var result = new SupportVectorMachine();
var ins0 = new EncogReadHelper(mask0);
EncogFileSection section;
while ((section = ins0.ReadNextSection()) != null)
{
if (section.SectionName.Equals("SVM")
&& section.SubSectionName.Equals("PARAMS"))
{
IDictionary<String, String> paras = section.ParseParams();
EngineArray.PutAll(paras, result.Properties);
}
if (section.SectionName.Equals("SVM")
&& section.SubSectionName.Equals("SVM-PARAM"))
{
IDictionary<String, String> p = section.ParseParams();
result.InputCount = EncogFileSection.ParseInt(p,
PersistConst.InputCount);
result.Params.C = EncogFileSection.ParseDouble(p,
ParamC);
result.Params.cache_size = EncogFileSection.ParseDouble(
p, ParamCacheSize);
result.Params.coef0 = EncogFileSection.ParseDouble(p,
ParamCoef0);
result.Params.degree = EncogFileSection.ParseDouble(p,
ParamDegree);
result.Params.eps = EncogFileSection.ParseDouble(p,
ParamEps);
result.Params.gamma = EncogFileSection.ParseDouble(p,
ParamGamma);
result.Params.kernel_type = EncogFileSection.ParseInt(
p, ParamKernelType);
result.Params.nr_weight = EncogFileSection.ParseInt(
p, ParamNumWeight);
result.Params.nu = EncogFileSection.ParseDouble(p,
ParamNu);
result.Params.p = EncogFileSection.ParseDouble(p,
ParamP);
result.Params.probability = EncogFileSection.ParseInt(
p, ParamProbability);
result.Params.shrinking = EncogFileSection.ParseInt(
p, ParamShrinking);
/*result.Params.statIterations = Encog.Persist.EncogFileSection.ParseInt(
params_0, PersistSVM.PARAM_START_ITERATIONS);*/
result.Params.svm_type = EncogFileSection.ParseInt(p,
ParamSVMType);
result.Params.weight = section.ParseDoubleArray(p, ParamWeight);
result.Params.weight_label = EncogFileSection
.ParseIntArray(p, ParamWeightLabel);
}
else if (section.SectionName.Equals("SVM")
&& section.SubSectionName.Equals("SVM-MODEL"))
{
try
{
var rdr = new StringReader(
section.LinesAsString);
TextReader br = rdr;
svm_model model = svm.svm_load_model(rdr);
result.Model = model;
br.Close();
rdr.Close();
}
catch (IOException ex)
{
throw new PersistError(ex);
}
}
}
return result;
}
public object Read(Stream mask0)
{
IDictionary<string, string> source = null;
EncogFileSection section;
IDictionary<string, string> dictionary2;
EncogReadHelper helper = new EncogReadHelper(mask0);
int theInputCount = 0;
int theInstarCount = 0;
int theOutstarCount = 0;
int theWinnerCount = 0;
Matrix other = null;
Matrix matrix2 = null;
goto Label_0097;
Label_0075:
if (3 == 0)
{
goto Label_00D0;
}
if ((((uint) theInstarCount) + ((uint) theOutstarCount)) > uint.MaxValue)
{
goto Label_019A;
}
Label_0097:
if ((section = helper.ReadNextSection()) != null)
{
if (!section.SectionName.Equals("CPN"))
{
goto Label_00D0;
}
goto Label_019A;
}
CPNNetwork network = new CPNNetwork(theInputCount, theInstarCount, theOutstarCount, theWinnerCount);
EngineArray.PutAll<string, string>(source, network.Properties);
if ((((uint) theInputCount) & 0) != 0)
{
goto Label_0176;
}
network.WeightsInputToInstar.Set(other);
network.WeightsInstarToOutstar.Set(matrix2);
if (((uint) theInstarCount) <= uint.MaxValue)
{
return network;
}
goto Label_00E4;
Label_00D0:
if (!section.SectionName.Equals("CPN"))
{
goto Label_0097;
}
if (((uint) theInstarCount) >= 0)
{
if (section.SubSectionName.Equals("NETWORK"))
{
dictionary2 = section.ParseParams();
theInputCount = EncogFileSection.ParseInt(dictionary2, "inputCount");
goto Label_0176;
}
if (((uint) theInstarCount) >= 0)
{
goto Label_0097;
}
goto Label_0075;
}
return network;
Label_00E4:
theWinnerCount = EncogFileSection.ParseInt(dictionary2, "winnerCount");
other = EncogFileSection.ParseMatrix(dictionary2, "inputToInstar");
matrix2 = EncogFileSection.ParseMatrix(dictionary2, "instarToInput");
if (2 != 0)
{
goto Label_0075;
}
goto Label_00D0;
Label_0176:
theInstarCount = EncogFileSection.ParseInt(dictionary2, "instar");
if (((uint) theWinnerCount) >= 0)
{
theOutstarCount = EncogFileSection.ParseInt(dictionary2, "outputCount");
if ((((uint) theInputCount) + ((uint) theInstarCount)) < 0)
{
goto Label_019A;
}
}
goto Label_00E4;
Label_019A:
if (section.SubSectionName.Equals("PARAMS"))
{
source = section.ParseParams();
}
goto Label_00D0;
}
public object Read(Stream mask0)
{
EncogReadHelper helper;
EncogFileSection section;
SOMNetwork network = new SOMNetwork();
goto Label_00FC;
Label_000B:
if (section.SubSectionName.Equals("NETWORK"))
{
IDictionary<string, string> paras = section.ParseParams();
network.Weights = EncogFileSection.ParseMatrix(paras, "weights");
network.OutputCount = EncogFileSection.ParseInt(paras, "outputCount");
network.InputCount = EncogFileSection.ParseInt(paras, "inputCount");
if (0 != 0)
{
if (0 == 0)
{
goto Label_0055;
}
goto Label_0039;
}
}
Label_001D:
if ((section = helper.ReadNextSection()) != null)
{
if (!section.SectionName.Equals("SOM"))
{
goto Label_003E;
}
goto Label_00A0;
}
if (15 != 0)
{
return network;
}
goto Label_00FC;
Label_0039:
if (0 == 0)
{
goto Label_001D;
}
goto Label_000B;
Label_003E:
if (!section.SectionName.Equals("SOM"))
{
goto Label_0039;
}
if (1 != 0)
{
goto Label_000B;
}
return network;
Label_0055:
if (0 != 0)
{
if (0 != 0)
{
goto Label_001D;
}
}
else
{
goto Label_003E;
}
Label_00A0:
if (section.SubSectionName.Equals("PARAMS"))
{
EngineArray.PutAll<string, string>(section.ParseParams(), network.Properties);
}
goto Label_003E;
Label_00FC:
if (4 == 0)
{
goto Label_0055;
}
helper = new EncogReadHelper(mask0);
goto Label_001D;
}
public object Read(Stream mask0)
{
EncogReadHelper helper;
EncogFileSection section;
IDictionary<string, string> dictionary;
TrainingContinuation continuation = new TrainingContinuation();
if (3 != 0)
{
helper = new EncogReadHelper(mask0);
goto Label_001E;
}
Label_0010:
if ((-2 == 0) || (4 == 0))
{
goto Label_005C;
}
Label_001E:
if ((section = helper.ReadNextSection()) == null)
{
return continuation;
}
if (!section.SectionName.Equals("CONT"))
{
if (1 != 0)
{
if (0xff == 0)
{
return continuation;
}
goto Label_0010;
}
if (0 == 0)
{
goto Label_0077;
}
goto Label_001E;
}
Label_005C:
if (section.SubSectionName.Equals("PARAMS"))
{
dictionary = section.ParseParams();
}
else if ((0 == 0) && ((0 != 0) || (3 != 0)))
{
goto Label_001E;
}
Label_0077:
using (IEnumerator<string> enumerator = dictionary.Keys.GetEnumerator())
{
string current;
double[] numArray;
goto Label_0090;
Label_0086:
continuation.Put(current, numArray);
Label_0090:
if (enumerator.MoveNext())
{
current = enumerator.Current;
if (current.Equals("type", StringComparison.InvariantCultureIgnoreCase))
{
continuation.TrainingType = dictionary[current];
goto Label_0090;
}
numArray = EncogFileSection.ParseDoubleArray(dictionary, current);
if (0xff != 0)
{
}
goto Label_0086;
}
}
goto Label_001E;
}
/// <inheritdoc/>
public Object Read(Stream istream)
{
int states = 0;
int[] items;
double[] pi = null;
Matrix transitionProbability = null;
IDictionary<String, String> properties = null;
IList<IStateDistribution> distributions = new List<IStateDistribution>();
EncogReadHelper reader = new EncogReadHelper(istream);
EncogFileSection section;
while ((section = reader.ReadNextSection()) != null)
{
if (section.SectionName.Equals("HMM")
&& section.SubSectionName.Equals("PARAMS"))
{
properties = section.ParseParams();
}
if (section.SectionName.Equals("HMM")
&& section.SubSectionName.Equals("CONFIG"))
{
IDictionary<String, String> p = section.ParseParams();
states = EncogFileSection.ParseInt(p, HiddenMarkovModel.TAG_STATES);
if (p.ContainsKey(HiddenMarkovModel.TAG_ITEMS))
{
items = EncogFileSection.ParseIntArray(p, HiddenMarkovModel.TAG_ITEMS);
}
pi = section.ParseDoubleArray(p, HiddenMarkovModel.TAG_PI);
transitionProbability = EncogFileSection.ParseMatrix(p, HiddenMarkovModel.TAG_TRANSITION);
}
else if (section.SectionName.Equals("HMM")
&& section.SubSectionName.StartsWith("DISTRIBUTION-"))
{
IDictionary<String, String> p = section.ParseParams();
String t = p[HiddenMarkovModel.TAG_DIST_TYPE];
if ("ContinousDistribution".Equals(t))
{
double[] mean = section.ParseDoubleArray(p, HiddenMarkovModel.TAG_MEAN);
Matrix cova = EncogFileSection.ParseMatrix(p, HiddenMarkovModel.TAG_COVARIANCE);
ContinousDistribution dist = new ContinousDistribution(mean, cova.Data);
distributions.Add(dist);
}
else if ("DiscreteDistribution".Equals(t))
{
Matrix prob = EncogFileSection.ParseMatrix(p, HiddenMarkovModel.TAG_PROBABILITIES);
DiscreteDistribution dist = new DiscreteDistribution(prob.Data);
distributions.Add(dist);
}
}
}
HiddenMarkovModel result = new HiddenMarkovModel(states);
EngineArray.PutAll(properties, result.Properties);
result.TransitionProbability = transitionProbability.Data;
result.Pi = pi;
int index = 0;
foreach (IStateDistribution dist in distributions)
{
result.StateDistributions[index++] = dist;
}
return result;
}
/// <summary>
/// Load an Encog script.
/// </summary>
/// <param name="stream">The stream to load from.</param>
public void Load(Stream stream)
{
EncogReadHelper reader = null;
try
{
EncogFileSection section;
reader = new EncogReadHelper(stream);
while ((section = reader.ReadNextSection()) != null)
{
ProcessSubSection(section);
}
// init the script
_script.Init();
}
finally
{
if (reader != null)
{
reader.Close();
}
}
}
/// <summary>
/// Read the object.
/// </summary>
/// <param name="mask0">The stream to read from.</param>
/// <returns>The loaded object.</returns>
public virtual Object Read(Stream mask0)
{
var result = new NEATNetwork();
var ins0 = new EncogReadHelper(mask0);
EncogFileSection section;
IDictionary<Int32, NEATNeuron> neuronMap = new Dictionary<Int32, NEATNeuron>();
while ((section = ins0.ReadNextSection()) != null)
{
if (section.SectionName.Equals("NEAT")
&& section.SubSectionName.Equals("PARAMS"))
{
IDictionary<String, String> paras = section.ParseParams();
foreach (String key in paras.Keys)
{
result.Properties.Add(key, paras[key]);
}
}
if (section.SectionName.Equals("NEAT")
&& section.SubSectionName.Equals("NETWORK"))
{
IDictionary<String, String> p = section.ParseParams();
result.InputCount = EncogFileSection.ParseInt(p,
PersistConst.InputCount);
result.OutputCount = EncogFileSection.ParseInt(p,
PersistConst.OutputCount);
result.ActivationFunction = EncogFileSection
.ParseActivationFunction(p,
PersistConst.ActivationFunction);
result.OutputActivationFunction = EncogFileSection
.ParseActivationFunction(p,
NEATPopulation.PropertyOutputActivation);
result.NetworkDepth = EncogFileSection.ParseInt(p,
PersistConst.Depth);
result.Snapshot = EncogFileSection.ParseBoolean(p,
PersistConst.Snapshot);
}
else if (section.SectionName.Equals("NEAT")
&& section.SubSectionName.Equals("NEURONS"))
{
foreach (String line in section.Lines)
{
IList<String> cols = EncogFileSection.SplitColumns(line);
long neuronID = Int32.Parse(cols[0]);
NEATNeuronType neuronType = PersistNEATPopulation
.StringToNeuronType(cols[1]);
double activationResponse = CSVFormat.EgFormat
.Parse(cols[2]);
double splitY = CSVFormat.EgFormat
.Parse(cols[3]);
double splitX = CSVFormat.EgFormat
.Parse(cols[4]);
var neatNeuron = new NEATNeuron(neuronType,
neuronID, splitY, splitX, activationResponse);
result.Neurons.Add(neatNeuron);
neuronMap[((int) neuronID)] = (neatNeuron);
}
}
else if (section.SectionName.Equals("NEAT")
&& section.SubSectionName.Equals("LINKS"))
{
foreach (String line in section.Lines)
{
IList<String> cols = EncogFileSection.SplitColumns(line);
int fromID = Int32.Parse(cols[0]);
int toID = Int32.Parse(cols[1]);
bool recurrent = Int32.Parse(cols[2]) > 0;
double weight = CSVFormat.EgFormat.Parse(cols[3]);
NEATNeuron fromNeuron = (neuronMap[fromID]);
NEATNeuron toNeuron = (neuronMap[toID]);
var neatLink = new NEATLink(weight, fromNeuron,
toNeuron, recurrent);
fromNeuron.OutputboundLinks.Add(neatLink);
toNeuron.InboundLinks.Add(neatLink);
}
}
}
return result;
}
/// <inheritdoc />
public Object Read(Stream istream)
{
var context = new EncogProgramContext();
var result = new PrgPopulation(context, 0);
var reader = new EncogReadHelper(istream);
EncogFileSection section;
int count = 0;
ISpecies lastSpecies = null;
while ((section = reader.ReadNextSection()) != null)
{
if (section.SectionName.Equals("BASIC")
&& section.SubSectionName.Equals("PARAMS"))
{
IDictionary<string, string> prms = section.ParseParams();
EngineArray.PutAll(prms, result.Properties);
}
else if (section.SectionName.Equals("BASIC")
&& section.SubSectionName.Equals("EPL-POPULATION"))
{
foreach (string line in section.Lines)
{
IList<String> cols = EncogFileSection.SplitColumns(line);
if (String.Compare(cols[0], "s", StringComparison.OrdinalIgnoreCase) == 0)
{
lastSpecies = new BasicSpecies
{
Age = int.Parse(cols[1]),
BestScore = CSVFormat.EgFormat.Parse(cols[2]),
Population = result,
GensNoImprovement = int.Parse(cols[3])
};
result.Species.Add(lastSpecies);
}
else if (cols[0].Equals("p"))
{
double score;
double adjustedScore;
if (String.Compare(cols[1], "nan", StringComparison.OrdinalIgnoreCase) == 0
|| String.Compare(cols[2], "nan", StringComparison.OrdinalIgnoreCase) == 0)
{
score = Double.NaN;
adjustedScore = Double.NaN;
}
else
{
score = CSVFormat.EgFormat.Parse(cols[1]);
adjustedScore = CSVFormat.EgFormat.Parse(cols[2]);
}
String code = cols[3];
var prg = new EncogProgram(context);
prg.CompileEPL(code);
prg.Score = score;
prg.Species = lastSpecies;
prg.AdjustedScore = adjustedScore;
if (lastSpecies == null)
{
throw new EncogError(
"Have not defined a species yet");
}
lastSpecies.Add(prg);
count++;
}
}
}
else if (section.SectionName.Equals("BASIC")
&& section.SubSectionName.Equals("EPL-OPCODES"))
{
foreach (String line in section.Lines)
{
IList<string> cols = EncogFileSection.SplitColumns(line);
String name = cols[0];
int args = int.Parse(cols[1]);
result.Context.Functions.AddExtension(name, args);
}
}
else if (section.SectionName.Equals("BASIC")
&& section.SubSectionName.Equals("EPL-SYMBOLIC"))
{
bool first = true;
foreach (string line in section.Lines)
{
if (!first)
{
IList<String> cols = EncogFileSection.SplitColumns(line);
String name = cols[0];
String t = cols[1];
var vt = EPLValueType.Unknown;
if (string.Compare(t, "f", true) == 0)
{
vt = EPLValueType.FloatingType;
}
else if (string.Compare(t, "b", true) == 0)
{
vt = EPLValueType.BooleanType;
}
else if (string.Compare(t, "i", true) == 0)
{
vt = EPLValueType.IntType;
}
else if (string.Compare(t, "s", true) == 0)
{
vt = EPLValueType.StringType;
}
else if (string.Compare(t, "e", true) == 0)
{
vt = EPLValueType.EnumType;
}
int enumType = int.Parse(cols[2]);
int enumCount = int.Parse(cols[3]);
var mapping = new VariableMapping(
name, vt, enumType, enumCount);
if (mapping.Name.Length > 0)
{
result.Context.DefineVariable(mapping);
}
else
{
result.Context.Result = mapping;
}
}
else
{
first = false;
}
}
}
}
result.PopulationSize = count;
// set the best genome, should be the first genome in the first species
if (result.Species.Count > 0)
{
ISpecies species = result.Species[0];
if (species.Members.Count > 0)
{
result.BestGenome = species.Members[0];
}
// set the leaders
foreach (ISpecies sp in result.Species)
{
if (sp.Members.Count > 0)
{
sp.Leader = sp.Members[0];
}
}
}
return result;
}
public object Read(Stream mask0)
{
EncogReadHelper helper;
EncogFileSection section;
IDictionary<string, string> dictionary2;
HopfieldNetwork network = new HopfieldNetwork();
goto Label_00F0;
Label_000D:
if (section.SectionName.Equals("HOPFIELD") || (0 != 0))
{
goto Label_0031;
}
Label_0022:
if ((section = helper.ReadNextSection()) != null)
{
if (section.SectionName.Equals("HOPFIELD"))
{
if (0 != 0)
{
goto Label_0031;
}
if (3 != 0)
{
if (0xff == 0)
{
goto Label_0022;
}
if (section.SubSectionName.Equals("PARAMS"))
{
IDictionary<string, string> source = section.ParseParams();
if (0 == 0)
{
EngineArray.PutAll<string, string>(source, network.Properties);
}
}
}
}
goto Label_000D;
}
return network;
Label_0031:
if (section.SubSectionName.Equals("NETWORK"))
{
dictionary2 = section.ParseParams();
}
else
{
goto Label_0022;
}
network.Weights = NumberList.FromList(CSVFormat.EgFormat, dictionary2["weights"]);
if (0 == 0)
{
network.SetCurrentState(NumberList.FromList(CSVFormat.EgFormat, dictionary2["output"]));
network.NeuronCount = EncogFileSection.ParseInt(dictionary2, "neurons");
goto Label_0022;
}
if (3 != 0)
{
goto Label_000D;
}
Label_00F0:
helper = new EncogReadHelper(mask0);
goto Label_0022;
}
public virtual object Read(Stream mask0)
{
EncogReadHelper helper;
EncogFileSection section;
IDictionary<int, NEATNeuron> dictionary;
IDictionary<string, string> dictionary2;
double num2;
double num3;
int num5;
int num6;
bool flag;
double num7;
NEATNetwork network = new NEATNetwork();
if ((((uint) flag) + ((uint) num3)) <= uint.MaxValue)
{
if ((((uint) num6) + ((uint) num6)) < 0)
{
goto Label_03FB;
}
if ((((uint) flag) + ((uint) num3)) <= uint.MaxValue)
{
helper = new EncogReadHelper(mask0);
if ((((uint) flag) & 0) == 0)
{
dictionary = new Dictionary<int, NEATNeuron>();
goto Label_0023;
}
}
goto Label_03AA;
}
goto Label_0035;
Label_0023:
if ((section = helper.ReadNextSection()) != null)
{
goto Label_045C;
}
return network;
Label_0035:
if (section.SectionName.Equals("NEAT"))
{
while (section.SubSectionName.Equals("LINKS"))
{
using (IEnumerator<string> enumerator3 = section.Lines.GetEnumerator())
{
string str3;
IList<string> list2;
NEATNeuron neuron3;
NEATLink link;
goto Label_007D;
Label_005B:
if ((((uint) num6) & 0) != 0)
{
goto Label_00D5;
}
neuron3.InboundLinks.Add(link);
Label_007D:
if (enumerator3.MoveNext())
{
goto Label_00FA;
}
if ((((uint) num2) + ((uint) num3)) >= 0)
{
goto Label_0023;
}
Label_009E:
num7 = CSVFormat.EgFormat.Parse(list2[3]);
NEATNeuron fromNeuron = dictionary[num5];
neuron3 = dictionary[num6];
link = new NEATLink(num7, fromNeuron, neuron3, flag);
Label_00D5:
fromNeuron.OutputboundLinks.Add(link);
if (((uint) num3) >= 0)
{
goto Label_005B;
}
goto Label_0023;
Label_00FA:
str3 = enumerator3.Current;
list2 = EncogFileSection.SplitColumns(str3);
num5 = int.Parse(list2[0]);
if (-2 != 0)
{
}
num6 = int.Parse(list2[1]);
flag = int.Parse(list2[2]) > 0;
goto Label_009E;
}
}
if (((uint) num7) >= 0)
{
}
}
goto Label_0023;
Label_03AA:
if (!section.SectionName.Equals("NEAT") || !section.SubSectionName.Equals("NETWORK"))
{
if (section.SectionName.Equals("NEAT") && section.SubSectionName.Equals("NEURONS"))
{
using (IEnumerator<string> enumerator2 = section.Lines.GetEnumerator())
{
string str2;
IList<string> list;
long num;
NEATNeuronType type;
NEATNeuron neuron;
Label_01BD:
if (enumerator2.MoveNext())
{
goto Label_0257;
}
goto Label_0023;
Label_01CE:
if ((((uint) num) + ((uint) num5)) > uint.MaxValue)
{
goto Label_02A0;
}
network.Neurons.Add(neuron);
dictionary[(int) num] = neuron;
goto Label_02D0;
Label_0206:
num3 = CSVFormat.EgFormat.Parse(list[3]);
double num4 = CSVFormat.EgFormat.Parse(list[4]);
neuron = new NEATNeuron(type, num, num3, num4, num2);
if ((((uint) num7) - ((uint) num)) <= uint.MaxValue)
{
goto Label_02B9;
}
Label_0257:
str2 = enumerator2.Current;
do
{
list = EncogFileSection.SplitColumns(str2);
num = int.Parse(list[0]);
type = PersistNEATPopulation.StringToNeuronType(list[1]);
}
while ((((uint) num) + ((uint) num5)) < 0);
Label_02A0:
num2 = CSVFormat.EgFormat.Parse(list[2]);
goto Label_0206;
Label_02B9:
if ((((uint) num3) & 0) == 0)
{
goto Label_01CE;
}
Label_02D0:
if ((((uint) num6) - ((uint) num4)) >= 0)
{
goto Label_01BD;
}
goto Label_0023;
}
}
goto Label_0035;
}
IDictionary<string, string> paras = section.ParseParams();
network.InputCount = EncogFileSection.ParseInt(paras, "inputCount");
network.OutputCount = EncogFileSection.ParseInt(paras, "outputCount");
network.ActivationFunction = EncogFileSection.ParseActivationFunction(paras, "activationFunction");
if (((uint) num7) <= uint.MaxValue)
{
network.OutputActivationFunction = EncogFileSection.ParseActivationFunction(paras, "outAct");
if (((uint) num3) >= 0)
{
network.NetworkDepth = EncogFileSection.ParseInt(paras, "depth");
network.Snapshot = EncogFileSection.ParseBoolean(paras, "snapshot");
goto Label_0023;
}
goto Label_0035;
}
Label_03F3:
dictionary2 = section.ParseParams();
Label_03FB:
foreach (string str in dictionary2.Keys)
{
network.Properties.Add(str, dictionary2[str]);
}
goto Label_03AA;
if (((((uint) flag) + ((uint) num2)) <= uint.MaxValue) && (((uint) flag) >= 0))
{
goto Label_03AA;
}
Label_045C:
if (section.SectionName.Equals("NEAT") && section.SubSectionName.Equals("PARAMS"))
{
goto Label_03F3;
}
goto Label_03AA;
}
public object Read(Stream mask0)
{
EncogReadHelper helper;
EncogFileSection section;
ART1 art = new ART1();
goto Label_01A7;
Label_0014:
if (0 != 0)
{
goto Label_005C;
}
Label_0020:
if ((section = helper.ReadNextSection()) != null)
{
if (section.SectionName.Equals("ART1") && (section.SubSectionName.Equals("PARAMS") || (0 != 0)))
{
EngineArray.PutAll<string, string>(section.ParseParams(), art.Properties);
}
goto Label_0048;
}
return art;
Label_0041:
if ((-2 != 0) && (15 != 0))
{
if (0xff == 0)
{
goto Label_0014;
}
goto Label_0020;
}
Label_0048:
if (!section.SectionName.Equals("ART1"))
{
goto Label_0014;
}
Label_005C:
if (section.SubSectionName.Equals("NETWORK"))
{
IDictionary<string, string> dictionary2;
Label_0166:
dictionary2 = section.ParseParams();
if (0 == 0)
{
art.A1 = EncogFileSection.ParseDouble(dictionary2, "A1");
art.B1 = EncogFileSection.ParseDouble(dictionary2, "B1");
art.C1 = EncogFileSection.ParseDouble(dictionary2, "C1");
if (0 == 0)
{
art.D1 = EncogFileSection.ParseDouble(dictionary2, "D1");
art.F1Count = EncogFileSection.ParseInt(dictionary2, "f1Count");
if (4 != 0)
{
if (0 != 0)
{
goto Label_0041;
}
if (0 != 0)
{
goto Label_0166;
}
art.F2Count = EncogFileSection.ParseInt(dictionary2, "f2Count");
art.NoWinner = EncogFileSection.ParseInt(dictionary2, "noWinner");
}
art.L = EncogFileSection.ParseDouble(dictionary2, "L");
art.Vigilance = EncogFileSection.ParseDouble(dictionary2, "VIGILANCE");
}
art.WeightsF1ToF2 = EncogFileSection.ParseMatrix(dictionary2, "weightsF1F2");
art.WeightsF2ToF1 = EncogFileSection.ParseMatrix(dictionary2, "weightsF2F1");
goto Label_0041;
}
}
else
{
goto Label_0020;
}
Label_01A7:
helper = new EncogReadHelper(mask0);
goto Label_0020;
}
public object Read(Stream mask0)
{
EncogFileSection section;
IDictionary<string, string> dictionary;
IDictionary<string, string> dictionary2;
int num;
int num2;
int num3;
int num4;
int num5;
int num6;
RBFNetwork network = new RBFNetwork();
FlatNetworkRBF flat = (FlatNetworkRBF) network.Flat;
EncogReadHelper helper = new EncogReadHelper(mask0);
Label_003B:
if ((section = helper.ReadNextSection()) != null)
{
if (!section.SectionName.Equals("RBF-NETWORK"))
{
goto Label_0473;
}
goto Label_069F;
}
if ((((uint) num5) & 0) == 0)
{
goto Label_0236;
}
goto Label_0070;
Label_005E:
if (!section.SectionName.Equals("RBF-NETWORK"))
{
goto Label_003B;
}
Label_0070:
if (section.SubSectionName.Equals("RBF"))
{
num3 = 0;
num4 = flat.LayerCounts[1];
do
{
if (0 != 0)
{
if ((((uint) num6) - ((uint) num2)) < 0)
{
goto Label_0473;
}
goto Label_0416;
}
}
while ((((uint) num3) - ((uint) num3)) > uint.MaxValue);
num5 = flat.LayerCounts[2];
if ((((uint) num4) | 0xfffffffe) == 0)
{
goto Label_0473;
}
goto Label_0273;
}
if ((((uint) num) + ((uint) num)) > uint.MaxValue)
{
goto Label_02F4;
}
if ((((uint) num2) - ((uint) num5)) >= 0)
{
if (((((uint) num4) - ((uint) num3)) > uint.MaxValue) && ((((uint) num5) - ((uint) num5)) < 0))
{
goto Label_005E;
}
goto Label_003B;
}
Label_0236:
if ((((uint) num3) + ((uint) num4)) >= 0)
{
return network;
}
if (4 != 0)
{
goto Label_02F4;
}
if ((((uint) num) + ((uint) num5)) >= 0)
{
goto Label_005E;
}
Label_0273:
flat.RBF = new IRadialBasisFunction[num4];
if (((uint) num2) >= 0)
{
if ((((uint) num5) | 0xfffffffe) == 0)
{
return network;
}
using (IEnumerator<string> enumerator2 = section.Lines.GetEnumerator())
{
string str3;
IRadialBasisFunction function2;
IList<string> list2;
goto Label_00EC;
Label_00D6:
if (num6 < num5)
{
goto Label_00FF;
}
Label_00DC:
flat.RBF[num3++] = function2;
Label_00EC:
if (enumerator2.MoveNext())
{
goto Label_01F2;
}
goto Label_003B;
Label_00FA:
num6 = 0;
goto Label_00D6;
Label_00FF:
function2.Centers[num6] = CSVFormat.EgFormat.Parse(list2[num6 + 3]);
Label_011E:
num6++;
if (0 == 0)
{
goto Label_00D6;
}
goto Label_003B;
Label_012C:
function2.Centers = new double[num5];
goto Label_00FA;
Label_013F:
if (0 != 0)
{
goto Label_011E;
}
list2 = EncogFileSection.SplitColumns(str3);
string name = "Encog.MathUtil.RBF." + list2[0];
try
{
function2 = (IRadialBasisFunction) ReflectionUtil.LoadObject(name);
}
catch (TypeLoadException exception2)
{
throw new PersistError(exception2);
}
catch (TargetException exception3)
{
throw new PersistError(exception3);
}
catch (MemberAccessException exception4)
{
throw new PersistError(exception4);
}
function2.Width = CSVFormat.EgFormat.Parse(list2[1]);
function2.Peak = CSVFormat.EgFormat.Parse(list2[2]);
if ((((uint) num6) + ((uint) num)) >= 0)
{
goto Label_0200;
}
if ((((uint) num4) - ((uint) num3)) < 0)
{
goto Label_00DC;
}
Label_01F2:
str3 = enumerator2.Current;
goto Label_013F;
Label_0200:
if ((((uint) num4) | 3) != 0)
{
goto Label_012C;
}
goto Label_00FA;
}
}
Label_02F4:
using (IEnumerator<string> enumerator = section.Lines.GetEnumerator())
{
string str;
IActivationFunction function;
IList<string> list;
goto Label_0313;
Label_0303:
flat.ActivationFunctions[num++] = function;
Label_0313:
if (enumerator.MoveNext())
{
goto Label_03A2;
}
if (0xff != 0)
{
goto Label_003B;
}
Label_032B:
if (num2 < function.ParamNames.Length)
{
goto Label_0376;
}
goto Label_03AD;
Label_033A:
list = EncogFileSection.SplitColumns(str);
string str2 = "Encog.Engine.Network.Activation." + list[0];
try
{
function = (IActivationFunction) ReflectionUtil.LoadObject(str2);
}
catch (Exception exception)
{
throw new PersistError(exception);
}
num2 = 0;
goto Label_032B;
Label_0376:
function.Params[num2] = CSVFormat.EgFormat.Parse(list[num2 + 1]);
num2++;
goto Label_032B;
Label_03A2:
str = enumerator.Current;
goto Label_033A;
Label_03AD:
if ((((uint) num2) | uint.MaxValue) != 0)
{
goto Label_0303;
}
goto Label_003B;
}
goto Label_005E;
Label_0416:
if (!section.SectionName.Equals("RBF-NETWORK") || !section.SubSectionName.Equals("ACTIVATION"))
{
goto Label_005E;
}
if ((((uint) num2) | 4) == 0)
{
goto Label_069F;
}
num = 0;
Label_045E:
flat.ActivationFunctions = new IActivationFunction[flat.LayerCounts.Length];
goto Label_02F4;
Label_0473:
if (section.SectionName.Equals("RBF-NETWORK"))
{
goto Label_05FF;
}
goto Label_0416;
Label_05EB:
flat.InputCount = EncogFileSection.ParseInt(dictionary2, "inputCount");
flat.LayerCounts = EncogFileSection.ParseIntArray(dictionary2, "layerCounts");
if ((((uint) num) + ((uint) num3)) <= uint.MaxValue)
{
goto Label_06F4;
}
goto Label_06B4;
Label_05FF:
if (!section.SubSectionName.Equals("NETWORK"))
{
goto Label_0416;
}
dictionary2 = section.ParseParams();
flat.BeginTraining = EncogFileSection.ParseInt(dictionary2, "beginTraining");
flat.ConnectionLimit = EncogFileSection.ParseDouble(dictionary2, "connectionLimit");
flat.ContextTargetOffset = EncogFileSection.ParseIntArray(dictionary2, "contextTargetOffset");
flat.ContextTargetSize = EncogFileSection.ParseIntArray(dictionary2, "contextTargetSize");
flat.EndTraining = EncogFileSection.ParseInt(dictionary2, "endTraining");
flat.HasContext = EncogFileSection.ParseBoolean(dictionary2, "hasContext");
goto Label_05EB;
Label_069F:
if (section.SubSectionName.Equals("PARAMS"))
{
dictionary = section.ParseParams();
}
else if (0 == 0)
{
goto Label_06D9;
}
Label_06B4:
EngineArray.PutAll<string, string>(dictionary, network.Properties);
if ((((uint) num5) - ((uint) num5)) >= 0)
{
goto Label_0473;
}
Label_06D9:
if ((((uint) num) - ((uint) num3)) >= 0)
{
if (0 == 0)
{
goto Label_0473;
}
goto Label_05FF;
}
Label_06F4:
if (-2147483648 != 0)
{
flat.LayerFeedCounts = EncogFileSection.ParseIntArray(dictionary2, "layerFeedCounts");
if (((uint) num3) < 0)
{
goto Label_05EB;
}
flat.LayerContextCount = EncogFileSection.ParseIntArray(dictionary2, "layerContextCount");
flat.LayerIndex = EncogFileSection.ParseIntArray(dictionary2, "layerIndex");
if (0 == 0)
{
flat.LayerOutput = EncogFileSection.ParseDoubleArray(dictionary2, "output");
flat.LayerSums = new double[flat.LayerOutput.Length];
flat.OutputCount = EncogFileSection.ParseInt(dictionary2, "outputCount");
}
flat.WeightIndex = EncogFileSection.ParseIntArray(dictionary2, "weightIndex");
if ((((uint) num3) > uint.MaxValue) || ((((uint) num2) - ((uint) num2)) < 0))
{
goto Label_045E;
}
flat.Weights = EncogFileSection.ParseDoubleArray(dictionary2, "weights");
flat.BiasActivation = EncogFileSection.ParseDoubleArray(dictionary2, "biasActivation");
goto Label_003B;
}
return network;
}
/// <inheritdoc/>
public Object Read(Stream istream)
{
BayesianNetwork result = new BayesianNetwork();
EncogReadHelper input = new EncogReadHelper(istream);
EncogFileSection section;
String queryType = "";
String queryStr = "";
String contentsStr = "";
while ((section = input.ReadNextSection()) != null)
{
if (section.SectionName.Equals("BAYES-NETWORK")
&& section.SubSectionName.Equals("BAYES-PARAM"))
{
IDictionary<String, String> p = section.ParseParams();
queryType = p["queryType"];
queryStr = p["query"];
contentsStr = p["contents"];
}
if (section.SectionName.Equals("BAYES-NETWORK")
&& section.SubSectionName.Equals("BAYES-TABLE"))
{
result.Contents = contentsStr;
// first, define relationships (1st pass)
foreach (String line in section.Lines)
{
result.DefineRelationship(line);
}
result.FinalizeStructure();
// now define the probabilities (2nd pass)
foreach (String line in section.Lines)
{
result.DefineProbability(line);
}
}
if (section.SectionName.Equals("BAYES-NETWORK")
&& section.SubSectionName.Equals("BAYES-PROPERTIES"))
{
IDictionary<String, String> paras = section.ParseParams();
EngineArray.PutAll(paras, result.Properties);
}
}
// define query, if it exists
if (queryType.Length > 0)
{
IBayesianQuery query = null;
if (queryType.Equals("EnumerationQuery"))
{
query = new EnumerationQuery(result);
}
else
{
query = new SamplingQuery(result);
}
if (query != null && queryStr.Length > 0)
{
result.Query = query;
result.DefineClassificationStructure(queryStr);
}
}
return result;
}
/// <summary>
/// Read the object.
/// </summary>
/// <param name="mask0">The stream to read the object from.</param>
/// <returns>The object that was loaded.</returns>
public virtual Object Read(Stream mask0)
{
var result = new NEATPopulation();
var innovationList = new NEATInnovationList {Population = result};
result.Innovations = innovationList;
var ins0 = new EncogReadHelper(mask0);
IDictionary<Int32, ISpecies> speciesMap = new Dictionary<Int32, ISpecies>();
IDictionary<ISpecies, Int32> leaderMap = new Dictionary<ISpecies, Int32>();
IDictionary<Int32, IGenome> genomeMap = new Dictionary<Int32, IGenome>();
EncogFileSection section;
while ((section = ins0.ReadNextSection()) != null)
{
if (section.SectionName.Equals("NEAT-POPULATION")
&& section.SubSectionName.Equals("INNOVATIONS"))
{
foreach (String line in section.Lines)
{
IList<String> cols = EncogFileSection.SplitColumns(line);
var innovation = new NEATInnovation
{
InnovationID = Int32.Parse(cols[0]),
InnovationType = StringToInnovationType(cols[1]),
NeuronType = StringToNeuronType(cols[2]),
SplitX = CSVFormat.EgFormat.Parse(cols[3]),
SplitY = CSVFormat.EgFormat.Parse(cols[4]),
NeuronID = Int32.Parse(cols[5]),
FromNeuronID = Int32.Parse(cols[6]),
ToNeuronID = Int32.Parse(cols[7])
};
result.Innovations.Add(innovation);
}
}
else if (section.SectionName.Equals("NEAT-POPULATION")
&& section.SubSectionName.Equals("SPECIES"))
{
foreach (String line in section.Lines)
{
String[] cols = line.Split(',');
var species = new BasicSpecies
{
SpeciesID = Int32.Parse(cols[0]),
Age = Int32.Parse(cols[1]),
BestScore = CSVFormat.EgFormat.Parse(cols[2]),
GensNoImprovement = Int32.Parse(cols[3]),
SpawnsRequired = CSVFormat.EgFormat
.Parse(cols[4])
};
species.SpawnsRequired = CSVFormat.EgFormat
.Parse(cols[5]);
leaderMap[(species)] = (Int32.Parse(cols[6]));
result.Species.Add(species);
speciesMap[((int) species.SpeciesID)] = (species);
}
}
else if (section.SectionName.Equals("NEAT-POPULATION")
&& section.SubSectionName.Equals("GENOMES"))
{
NEATGenome lastGenome = null;
foreach (String line in section.Lines)
{
IList<String> cols = EncogFileSection.SplitColumns(line);
if (cols[0].Equals("g", StringComparison.InvariantCultureIgnoreCase))
{
lastGenome = new NEATGenome
{
NeuronsChromosome = new Chromosome(),
LinksChromosome = new Chromosome()
};
lastGenome.Chromosomes.Add(lastGenome.NeuronsChromosome);
lastGenome.Chromosomes.Add(lastGenome.LinksChromosome);
lastGenome.GenomeID = Int32.Parse(cols[1]);
lastGenome.SpeciesID = Int32.Parse(cols[2]);
lastGenome.AdjustedScore = CSVFormat.EgFormat
.Parse(cols[3]);
lastGenome.AmountToSpawn = CSVFormat.EgFormat
.Parse(cols[4]);
lastGenome.NetworkDepth = Int32.Parse(cols[5]);
lastGenome.Score = CSVFormat.EgFormat.Parse(cols[6]);
result.Add(lastGenome);
genomeMap[(int) lastGenome.GenomeID] = lastGenome;
}
else if (cols[0].Equals("n", StringComparison.InvariantCultureIgnoreCase))
{
var neuronGene = new NEATNeuronGene
{
Id = Int32.Parse(cols[1]),
NeuronType = StringToNeuronType(cols[2]),
Enabled = Int32.Parse(cols[3]) > 0,
InnovationId = Int32.Parse(cols[4]),
ActivationResponse = CSVFormat.EgFormat
.Parse(cols[5]),
SplitX = CSVFormat.EgFormat.Parse(cols[6]),
SplitY = CSVFormat.EgFormat.Parse(cols[7])
};
lastGenome.Neurons.Add(neuronGene);
}
else if (cols[0].Equals("l", StringComparison.InvariantCultureIgnoreCase))
{
var linkGene = new NEATLinkGene();
linkGene.Id = Int32.Parse(cols[1]);
linkGene.Enabled = Int32.Parse(cols[2]) > 0;
linkGene.Recurrent = Int32.Parse(cols[3]) > 0;
linkGene.FromNeuronID = Int32.Parse(cols[4]);
linkGene.ToNeuronID = Int32.Parse(cols[5]);
linkGene.Weight = CSVFormat.EgFormat.Parse(cols[6]);
linkGene.InnovationId = Int32.Parse(cols[7]);
lastGenome.Links.Add(linkGene);
}
}
}
else if (section.SectionName.Equals("NEAT-POPULATION")
&& section.SubSectionName.Equals("CONFIG"))
{
IDictionary<String, String> paras = section.ParseParams();
result.NeatActivationFunction = EncogFileSection
.ParseActivationFunction(paras,
NEATPopulation.PropertyNEATActivation);
result.OutputActivationFunction = EncogFileSection
.ParseActivationFunction(paras,
NEATPopulation.PropertyOutputActivation);
result.Snapshot = EncogFileSection.ParseBoolean(paras,
PersistConst.Snapshot);
result.InputCount = EncogFileSection.ParseInt(paras,
PersistConst.InputCount);
result.OutputCount = EncogFileSection.ParseInt(paras,
PersistConst.OutputCount);
result.OldAgePenalty = EncogFileSection.ParseDouble(paras,
PopulationConst.PropertyOldAgePenalty);
result.OldAgeThreshold = EncogFileSection.ParseInt(paras,
PopulationConst.PropertyOldAgeThreshold);
result.PopulationSize = EncogFileSection.ParseInt(paras,
PopulationConst.PropertyPopulationSize);
result.SurvivalRate = EncogFileSection.ParseDouble(paras,
PopulationConst.PropertySurvivalRate);
result.YoungBonusAgeThreshhold = EncogFileSection.ParseInt(
paras, PopulationConst.PropertyYoungAgeThreshold);
result.YoungScoreBonus = EncogFileSection.ParseDouble(paras,
PopulationConst.PropertyYoungAgeBonus);
result.GenomeIDGenerate.CurrentID = EncogFileSection.ParseInt(paras,
PopulationConst.
PropertyNextGenomeID);
result.InnovationIDGenerate.CurrentID = EncogFileSection.ParseInt(paras,
PopulationConst.
PropertyNextInnovationID);
result.GeneIDGenerate.CurrentID = EncogFileSection.ParseInt(paras,
PopulationConst.
PropertyNextGeneID);
result.SpeciesIDGenerate.CurrentID = EncogFileSection.ParseInt(paras,
PopulationConst.
PropertyNextSpeciesID);
}
}
// now link everything up
// first put all the genomes into correct species
foreach (IGenome genome in result.Genomes)
{
var neatGenome = (NEATGenome) genome;
var speciesId = (int) neatGenome.SpeciesID;
if( speciesMap.ContainsKey(speciesId))
{
ISpecies s = speciesMap[speciesId];
s.Members.Add(neatGenome);
}
neatGenome.InputCount = result.InputCount;
neatGenome.OutputCount = result.OutputCount;
}
// set the species leader links
foreach (ISpecies species in leaderMap.Keys)
{
int leaderID = leaderMap[species];
IGenome leader = genomeMap[leaderID];
species.Leader = leader;
((BasicSpecies) species).Population = result;
}
return result;
}
public object Read(Stream mask0)
{
EncogFileSection section;
IDictionary<string, string> dictionary2;
BoltzmannMachine machine = new BoltzmannMachine();
EncogReadHelper helper = new EncogReadHelper(mask0);
Label_0034:
if ((section = helper.ReadNextSection()) != null)
{
goto Label_012B;
}
return machine;
Label_00A3:
machine.Threshold = NumberList.FromList(CSVFormat.EgFormat, dictionary2["thresholds"]);
machine.AnnealCycles = EncogFileSection.ParseInt(dictionary2, "annealCycles");
machine.RunCycles = EncogFileSection.ParseInt(dictionary2, "runCycles");
if (0 == 0)
{
machine.Temperature = EncogFileSection.ParseDouble(dictionary2, "temperature");
goto Label_0034;
}
goto Label_0142;
Label_00C4:
if (section.SectionName.Equals("BOLTZMANN") && section.SubSectionName.Equals("NETWORK"))
{
dictionary2 = section.ParseParams();
machine.Weights = NumberList.FromList(CSVFormat.EgFormat, dictionary2["weights"]);
}
else
{
goto Label_0034;
}
machine.SetCurrentState(NumberList.FromList(CSVFormat.EgFormat, dictionary2["output"]));
machine.NeuronCount = EncogFileSection.ParseInt(dictionary2, "neurons");
goto Label_00A3;
Label_012B:
if (!section.SectionName.Equals("BOLTZMANN"))
{
goto Label_00C4;
}
Label_0142:
if (section.SubSectionName.Equals("PARAMS"))
{
EngineArray.PutAll<string, string>(section.ParseParams(), machine.Properties);
if (0 == 0)
{
goto Label_00C4;
}
goto Label_012B;
}
if (0 != 0)
{
goto Label_0142;
}
if (2 == 0)
{
if (-1 == 0)
{
goto Label_00A3;
}
if (8 != 0)
{
goto Label_012B;
}
goto Label_0142;
}
goto Label_00C4;
}
public object Read(Stream mask0)
{
EncogReadHelper helper;
EncogFileSection section;
IDictionary<string, string> dictionary2;
SupportVectorMachine machine = new SupportVectorMachine();
goto Label_0306;
Label_000B:
if (section.SubSectionName.Equals("SVM-MODEL"))
{
try
{
svm_model _model;
StringReader fp = new StringReader(section.LinesAsString);
TextReader reader2 = fp;
if (0 == 0)
{
_model = svm.svm_load_model(fp);
}
machine.Model = _model;
reader2.Close();
fp.Close();
}
catch (IOException exception)
{
throw new PersistError(exception);
}
}
Label_001D:
if ((section = helper.ReadNextSection()) != null)
{
goto Label_028D;
}
return machine;
Label_002F:
if (!section.SectionName.Equals("SVM"))
{
goto Label_001D;
}
if (-2 == 0)
{
goto Label_023F;
}
if (3 != 0)
{
goto Label_000B;
}
return machine;
Label_0237:
dictionary2 = section.ParseParams();
Label_023F:
machine.InputCount = EncogFileSection.ParseInt(dictionary2, "inputCount");
machine.Params.C = EncogFileSection.ParseDouble(dictionary2, "C");
machine.Params.cache_size = EncogFileSection.ParseDouble(dictionary2, "cacheSize");
if (0 == 0)
{
if (0 == 0)
{
while (true)
{
machine.Params.coef0 = EncogFileSection.ParseDouble(dictionary2, "coef0");
machine.Params.degree = EncogFileSection.ParseDouble(dictionary2, "degree");
machine.Params.eps = EncogFileSection.ParseDouble(dictionary2, "eps");
machine.Params.gamma = EncogFileSection.ParseDouble(dictionary2, "gamma");
machine.Params.kernel_type = EncogFileSection.ParseInt(dictionary2, "kernelType");
machine.Params.nr_weight = EncogFileSection.ParseInt(dictionary2, "nrWeight");
machine.Params.nu = EncogFileSection.ParseDouble(dictionary2, "nu");
machine.Params.p = EncogFileSection.ParseDouble(dictionary2, "p");
if (0 == 0)
{
machine.Params.probability = EncogFileSection.ParseInt(dictionary2, "probability");
if (-2147483648 == 0)
{
goto Label_001D;
}
machine.Params.shrinking = EncogFileSection.ParseInt(dictionary2, "shrinking");
machine.Params.svm_type = EncogFileSection.ParseInt(dictionary2, "svmType");
machine.Params.weight = EncogFileSection.ParseDoubleArray(dictionary2, "weight");
machine.Params.weight_label = EncogFileSection.ParseIntArray(dictionary2, "weightLabel");
if (0xff != 0)
{
goto Label_001D;
}
goto Label_002F;
}
}
}
goto Label_000B;
}
if (0 == 0)
{
goto Label_0306;
}
Label_028D:
if (section.SectionName.Equals("SVM") && section.SubSectionName.Equals("PARAMS"))
{
IDictionary<string, string> source = section.ParseParams();
if (0x7fffffff == 0)
{
goto Label_0237;
}
EngineArray.PutAll<string, string>(source, machine.Properties);
}
if (section.SectionName.Equals("SVM") && section.SubSectionName.Equals("SVM-PARAM"))
{
if (8 != 0)
{
if (3 == 0)
{
goto Label_001D;
}
goto Label_0237;
}
}
else
{
goto Label_002F;
}
Label_0306:
helper = new EncogReadHelper(mask0);
goto Label_001D;
}
