/// <summary>
/// Creates the instance and initialize it from given xml element.
/// </summary>
/// <param name="elem">
/// Xml data containing settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public InputSynapseSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Network.SM.Synapse.InputSynapseSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement settingsElem = validator.Validate(elem, "rootElem");
//Parsing
XElement cfgElem;
//Spiking target
//Scope
cfgElem = settingsElem.XPathSelectElement("./spikingTarget");
if (cfgElem != null)
{
SpikingTargetScope = BaseSynapse.ParseSynapticTargetScope(cfgElem.Attribute("scope").Value);
}
else
{
SpikingTargetScope = BaseSynapse.SynapticTargetScope.Excitatory;
}
//Spiking target Weight
cfgElem = settingsElem.XPathSelectElement("./spikingTarget/weight");
if (cfgElem != null)
{
SpikingTargetWeightCfg = new RandomValueSettings(cfgElem);
}
else
{
SpikingTargetWeightCfg = new RandomValueSettings(0, 1);
}
//Analog target
//Scope
cfgElem = settingsElem.XPathSelectElement("./analogTarget");
if (cfgElem != null)
{
AnalogTargetScope = BaseSynapse.ParseSynapticTargetScope(cfgElem.Attribute("scope").Value);
}
else
{
AnalogTargetScope = BaseSynapse.SynapticTargetScope.All;
}
//Analog target Weight
cfgElem = settingsElem.XPathSelectElement("./analogTarget/weight");
if (cfgElem != null)
{
AnalogTargetWeightCfg = new RandomValueSettings(cfgElem);
}
else
{
AnalogTargetWeightCfg = new RandomValueSettings(0, 1);
}
//Delay
DelayMethod = BaseSynapse.ParseSynapticDelayMethod(settingsElem.Attribute("delayMethod").Value);
MaxDelay = int.Parse(settingsElem.Attribute("maxDelay").Value, CultureInfo.InvariantCulture);
return;
}
/// <summary>
/// Creates the instance and initialize it from given xml element.
/// This is the preferred way to instantiate settings.
/// </summary>
/// <param name="elem">
/// Xml data containing settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public FeedForwardNetworkSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Network.FF.FeedForwardNetworkSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement settingsElem = validator.Validate(elem, "rootElem");
//Parsing
OutputLayerActivation = ActivationFactory.LoadSettings(settingsElem.Descendants().First());
if (!IsAllowedActivation(OutputLayerActivation, out Interval outputRange))
{
throw new ApplicationException($"Activation can't be used in FF network. Activation function has to be stateless and has to support derivative calculation.");
}
OutputRange = outputRange;
//Hidden layers
HiddenLayerCollection = new List <HiddenLayerSettings>();
XElement hiddenLayersElem = settingsElem.Descendants("hiddenLayers").FirstOrDefault();
if (hiddenLayersElem != null)
{
foreach (XElement layerElem in hiddenLayersElem.Descendants("layer"))
{
HiddenLayerCollection.Add(new HiddenLayerSettings(layerElem));
}
}
//Trainer configuration
TrainerCfg = null;
foreach (XElement candidate in settingsElem.Descendants())
{
if (candidate.Name.LocalName == "qrdRegrTrainer")
{
TrainerCfg = new QRDRegrTrainerSettings(candidate);
}
else if (candidate.Name.LocalName == "ridgeRegrTrainer")
{
TrainerCfg = new RidgeRegrTrainerSettings(candidate);
}
else if (candidate.Name.LocalName == "elasticRegrTrainer")
{
TrainerCfg = new ElasticRegrTrainerSettings(candidate);
}
else if (candidate.Name.LocalName == "resPropTrainer")
{
TrainerCfg = new RPropTrainerSettings(candidate);
}
if (TrainerCfg != null)
{
break;
}
}
if (TrainerCfg == null)
{
throw new Exception("Trainer settings not found.");
}
return;
}
/// <summary>
/// Creates the instance and initialize it from given xml element.
/// This is the preferred way to instantiate reservoir settings.
/// </summary>
/// <param name="elem">
/// Xml data containing feed forward network settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public FeedForwardNetworkSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Network.FF.FeedForwardNetworkSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement feedForwardNetworkSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
OutputLayerActivation = new ActivationSettings(feedForwardNetworkSettingsElem.Descendants("outputActivation").First());
if (!IsAllowedActivation(OutputLayerActivation))
{
throw new ApplicationException($"Activation {OutputLayerActivation.FunctionType} can't be used in FF network. Activation function has to be stateless and has to support derivative calculation.");
}
RegressionMethod = ParseTrainingMethodType(feedForwardNetworkSettingsElem.Attribute("regressionMethod").Value);
//Hidden layers
HiddenLayerCollection = new List <HiddenLayerSettings>();
XElement hiddenLayersElem = feedForwardNetworkSettingsElem.Descendants("hiddenLayers").FirstOrDefault();
if (hiddenLayersElem != null)
{
foreach (XElement layerElem in hiddenLayersElem.Descendants("layer"))
{
HiddenLayerCollection.Add(new HiddenLayerSettings(layerElem));
}
}
//Trainers
LinRegrTrainerCfg = null;
RPropTrainerCfg = null;
switch (RegressionMethod)
{
case TrainingMethodType.Linear:
XElement linRegrTrainerElem = feedForwardNetworkSettingsElem.Descendants("linRegrTrainer").FirstOrDefault();
if (linRegrTrainerElem != null)
{
LinRegrTrainerCfg = new LinRegrTrainerSettings(linRegrTrainerElem);
}
else
{
LinRegrTrainerCfg = new LinRegrTrainerSettings();
}
break;
case TrainingMethodType.Resilient:
XElement resPropTrainerElem = feedForwardNetworkSettingsElem.Descendants("resPropTrainer").FirstOrDefault();
if (resPropTrainerElem != null)
{
RPropTrainerCfg = new RPropTrainerSettings(resPropTrainerElem);
}
else
{
RPropTrainerCfg = new RPropTrainerSettings();
}
break;
}
return;
}
/// <summary>
/// Creates an instance and initializes it from given xml element.
/// </summary>
/// <param name="elem">
/// Xml data containing RandomValueSettings settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public RandomValueSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RandomValue.RandomValueSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement randomValueSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
Min = double.Parse(randomValueSettingsElem.Attribute("min").Value, CultureInfo.InvariantCulture);
Max = double.Parse(randomValueSettingsElem.Attribute("max").Value, CultureInfo.InvariantCulture);
RandomSign = bool.Parse(randomValueSettingsElem.Attribute("randomSign").Value);
XElement distrParamsElem = randomValueSettingsElem.Elements().FirstOrDefault();
if (distrParamsElem == null)
{
DistrType = RandomExtensions.DistributionType.Uniform;
DistrCfg = new UniformDistrSettings();
}
else
{
switch (distrParamsElem.Name.LocalName)
{
case "uniformDistr":
DistrType = RandomExtensions.DistributionType.Uniform;
DistrCfg = new UniformDistrSettings(distrParamsElem);
break;
case "gaussianDistr":
DistrType = RandomExtensions.DistributionType.Gaussian;
DistrCfg = new GaussianDistrSettings(distrParamsElem);
break;
case "exponentialDistr":
DistrType = RandomExtensions.DistributionType.Exponential;
DistrCfg = new ExponentialDistrSettings(distrParamsElem);
break;
case "gammaDistr":
DistrType = RandomExtensions.DistributionType.Gamma;
DistrCfg = new GammaDistrSettings(distrParamsElem);
break;
default:
throw new Exception($"Unexpected element {distrParamsElem.Name.LocalName}");
}
}
Check();
return;
}
/// <summary>
/// Creates the instance and initializes it from given xml element.
/// Content of xml element is always validated against the xml schema.
/// </summary>
/// <param name="elem">Xml data containing settings</param>
public BinFeatureFilterSettings(XElement elem)
: base(BaseFeatureFilter.FeatureType.Binary)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Data.Filter.BinFeatureFilterSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement settingsElem = validator.Validate(elem, "rootElem");
return;
}
/// <summary>
/// Creates an instance and initializes it from given xml element.
/// </summary>
/// <param name="elem">
/// Xml data containing Sigmoid activation settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public SigmoidSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Activation.SigmoidSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement activationSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
return;
}
/// <summary>
/// Creates an instance and initializes it from given xml element.
/// </summary>
/// <param name="elem">
/// Xml data containing SoftExponential activation settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public SoftExponentialSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Activation.SoftExponentialSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement activationSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
Alpha = RandomValueSettings.LoadOrDefault(activationSettingsElem, "alpha", TypicalAlpha);
return;
}
/// <summary>
/// Creates an instance and initializes it from given xml element.
/// </summary>
/// <param name="elem">
/// Xml data containing ISRU activation settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public ISRUSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Activation.ISRUSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement activationSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
Alpha = new RandomValueSettings(activationSettingsElem.Descendants("alpha").FirstOrDefault());
return;
}
/// <summary>
/// Creates the instance and initializes it from given xml element.
/// Content of xml element is always validated against the xml schema.
/// </summary>
/// <param name="elem">Xml data containing settings</param>
public ConstGeneratorSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Data.Generators.ConstGeneratorSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement settingsElem = validator.Validate(elem, "rootElem");
//Parsing
ConstSignal = double.Parse(settingsElem.Attribute("constSignal").Value, CultureInfo.InvariantCulture);
return;
}
/// <summary>
/// Creates an instance and initializes it from given xml element.
/// </summary>
/// <param name="elem">
/// Xml data containing LeakyReLU activation settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public LeakyReLUSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Activation.LeakyReLUSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement activationSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
NegSlope = RandomValueSettings.LoadOrDefault(activationSettingsElem, "negSlope", TypicalNegSlope);
return;
}
/// <summary>
/// Creates the instance and initializes it from given xml element.
/// Content of xml element is always validated against the xml schema.
/// </summary>
/// <param name="elem">Xml data containing linear regression trainer settings</param>
public RidgeRegrTrainerSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Network.FF.RidgeRegrTrainerSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement settingsElem = validator.Validate(elem, "rootElem");
//Parsing
NumOfAttemptEpochs = int.Parse(settingsElem.Attribute("attemptEpochs").Value, CultureInfo.InvariantCulture);
LambdaSeekerCfg = new ParamSeekerSettings(settingsElem.Descendants("lambda").First());
return;
}
/// <summary>
/// Creates the instance and initialize it from given xml element.
/// </summary>
/// <param name="elem">
/// Xml data containing settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public StaticSynapseSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Network.SM.Synapse.StaticSynapseSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement settingsElem = validator.Validate(elem, "rootElem");
//Parsing
//Weight
WeightCfg = new RandomValueSettings(settingsElem.Descendants("weight").First());
return;
}
/// <summary>
/// Creates the instance and initializes it from given xml element.
/// Content of xml element is always validated against the xml schema.
/// </summary>
/// <param name="elem">Xml data containing settings</param>
public EnumFeatureFilterSettings(XElement elem)
: base(BaseFeatureFilter.FeatureType.Enum)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Data.Filter.EnumFeatureFilterSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement settingsElem = validator.Validate(elem, "rootElem");
//Parsing
NumOfElements = int.Parse(settingsElem.Attribute("numOfElements").Value, CultureInfo.InvariantCulture);
return;
}
/// <summary>
/// Creates the instance and initializes it from given xml element.
/// Content of xml element is always validated against the xml schema.
/// </summary>
/// <param name="elem">Xml data containing linear regression trainer settings</param>
public LinRegrTrainerSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Network.FF.LinRegrTrainerSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement linRegrTrainerSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
HiNoiseIntensity = double.Parse(linRegrTrainerSettingsElem.Attribute("hiNoiseIntensity").Value, CultureInfo.InvariantCulture);
MaxStretch = double.Parse(linRegrTrainerSettingsElem.Attribute("maxStretch").Value, CultureInfo.InvariantCulture);
ZeroMargin = double.Parse(linRegrTrainerSettingsElem.Attribute("zeroMargin").Value, CultureInfo.InvariantCulture);
return;
}
/// <summary>
/// Creates the instance and initializes it from given xml element.
/// Content of xml element is always validated against the xml schema.
/// </summary>
/// <param name="elem">Xml data containing the settings</param>
public ParamSeekerSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.MathTools.PS.ParamSeekerSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement linRegrTrainerSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
Min = double.Parse(linRegrTrainerSettingsElem.Attribute("min").Value, CultureInfo.InvariantCulture);
Max = double.Parse(linRegrTrainerSettingsElem.Attribute("max").Value, CultureInfo.InvariantCulture);
NumOfSteps = int.Parse(linRegrTrainerSettingsElem.Attribute("steps").Value, CultureInfo.InvariantCulture);
return;
}
/// <summary>
/// Creates the instance and initializes it from given xml element.
/// Content of xml element is always validated against the xml schema.
/// </summary>
/// <param name="elem">Xml data containing settings</param>
public SinusoidalGeneratorSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Data.Generators.SinusoidalGeneratorSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement settingsElem = validator.Validate(elem, "rootElem");
//Parsing
Phase = double.Parse(settingsElem.Attribute("phase").Value, CultureInfo.InvariantCulture);
Freq = double.Parse(settingsElem.Attribute("freq").Value, CultureInfo.InvariantCulture);
Ampl = double.Parse(settingsElem.Attribute("ampl").Value, CultureInfo.InvariantCulture);
return;
}
/// <summary>
/// Creates the instance and initializes it from given xml element.
/// Content of xml element is always validated against the xml schema.
/// </summary>
/// <param name="elem">Xml data containing elastic linear regression trainer settings</param>
public ElasticRegrTrainerSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Network.FF.ElasticRegrTrainerSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement settingsElem = validator.Validate(elem, "rootElem");
//Parsing
NumOfAttemptEpochs = int.Parse(settingsElem.Attribute("attemptEpochs").Value, CultureInfo.InvariantCulture);
Lambda = double.Parse(settingsElem.Attribute("lambda").Value, CultureInfo.InvariantCulture);
Alpha = double.Parse(settingsElem.Attribute("alpha").Value, CultureInfo.InvariantCulture);
return;
}
/// <summary>
/// Creates the instance and initializes it from given xml element.
/// Content of xml element is always validated against the xml schema.
/// </summary>
/// <param name="elem">Xml data containing settings</param>
public RealFeatureFilterSettings(XElement elem)
: base(BaseFeatureFilter.FeatureType.Real)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Data.Filter.RealFeatureFilterSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement settingsElem = validator.Validate(elem, "rootElem");
//Parsing
Standardize = bool.Parse(settingsElem.Attribute("standardize").Value);
KeepReserve = bool.Parse(settingsElem.Attribute("keepReserve").Value);
return;
}
/// <summary>
/// Creates the instance and initializes it from given xml element.
/// Content of xml element is always validated against the xml schema.
/// </summary>
/// <param name="elem">Xml data containing settings</param>
public PulseGeneratorSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Data.Generators.PulseGeneratorSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement settingsElem = validator.Validate(elem, "rootElem");
//Parsing
Signal = double.Parse(settingsElem.Attribute("signal").Value, CultureInfo.InvariantCulture);
AvgPeriod = Math.Abs(double.Parse(settingsElem.Attribute("avgPeriod").Value, CultureInfo.InvariantCulture));
Mode = ParseTimingMode(settingsElem.Attribute("mode").Value);
return;
}
/// <summary>
/// Creates the instance and initialize it from given xml element.
/// This is the preferred way to instantiate reservoir settings.
/// </summary>
/// <param name="elem">
/// Xml data containing reservoir settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public ReservoirSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Network.SM.Preprocessing.ReservoirSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement reservoirSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
SettingsName = reservoirSettingsElem.Attribute("name").Value;
SynapticDelayMethod = CommonEnums.ParseSynapticDelayMethod(reservoirSettingsElem.Attribute("synapticDelayMethod").Value);
MaxInputDelay = int.Parse(reservoirSettingsElem.Attribute("maxInputDelay").Value, CultureInfo.InvariantCulture);
MaxInternalDelay = int.Parse(reservoirSettingsElem.Attribute("maxInternalDelay").Value, CultureInfo.InvariantCulture);
SpectralRadius = reservoirSettingsElem.Attribute("spectralRadius").Value == "NA" ? -1d : double.Parse(reservoirSettingsElem.Attribute("spectralRadius").Value, CultureInfo.InvariantCulture);
//Input entry point
InputEntryPoint = new int[3];
if (reservoirSettingsElem.Descendants("inputEntryPoint").Count() > 0)
{
InputEntryPoint[0] = int.Parse(reservoirSettingsElem.Descendants("inputEntryPoint").First().Attribute("x").Value, CultureInfo.InvariantCulture);
InputEntryPoint[1] = int.Parse(reservoirSettingsElem.Descendants("inputEntryPoint").First().Attribute("y").Value, CultureInfo.InvariantCulture);
InputEntryPoint[2] = int.Parse(reservoirSettingsElem.Descendants("inputEntryPoint").First().Attribute("z").Value, CultureInfo.InvariantCulture);
}
else
{
InputEntryPoint.Populate(0);
}
//Pool settings collection
PoolSettingsCollection = new List <PoolSettings>();
foreach (XElement poolSettingsElem in reservoirSettingsElem.Descendants("pools").First().Descendants("pool"))
{
PoolSettingsCollection.Add(new PoolSettings(poolSettingsElem));
}
//Pools interconnection settings
PoolsInterconnectionCollection = new List <PoolsInterconnection>();
XElement pool2PoolConnContainerElem = reservoirSettingsElem.Descendants("pool2PoolConns").FirstOrDefault();
if (pool2PoolConnContainerElem != null)
{
foreach (XElement poolsInterConnElem in pool2PoolConnContainerElem.Descendants("pool2PoolConn"))
{
PoolsInterconnectionCollection.Add(new PoolsInterconnection(poolsInterConnElem, PoolSettingsCollection));
}
}
return;
}
/// <summary>
/// Creates an instance and initializes it from given xml element.
/// </summary>
/// <param name="elem">
/// Xml data containing IzhikevichIF activation settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public AutoIzhikevichIFSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Activation.AutoIzhikevichIFSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement activationSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
Role = NeuronCommon.ParseNeuronRole(activationSettingsElem.Attribute("role").Value);
RefractoryPeriods = int.Parse(activationSettingsElem.Attribute("refractoryPeriods").Value, CultureInfo.InvariantCulture);
SolverMethod = ODENumSolver.ParseComputationMethodType(activationSettingsElem.Attribute("solverMethod").Value);
SolverCompSteps = int.Parse(activationSettingsElem.Attribute("solverCompSteps").Value, CultureInfo.InvariantCulture);
return;
}
/// <summary>
/// Creates an instance and initializes it from given xml element.
/// </summary>
/// <param name="elem">
/// Xml data containing RandomValueSettings settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public RandomValueSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RandomValue.RandomValueSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement randomValueSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
Min = double.Parse(randomValueSettingsElem.Attribute("min").Value, CultureInfo.InvariantCulture);
Max = double.Parse(randomValueSettingsElem.Attribute("max").Value, CultureInfo.InvariantCulture);
RandomSign = bool.Parse(randomValueSettingsElem.Attribute("randomSign").Value);
DistrType = RandomClassExtensions.ParseDistributionType(randomValueSettingsElem.Attribute("distribution").Value);
return;
}
/// <summary>
/// Creates the instance and initializes it from given xml element.
/// Content of xml element is always validated against the xml schema.
/// </summary>
/// <param name="elem">Xml data containing p-delta rule trainer settings</param>
public PDeltaRuleTrainerSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Network.PP.PDeltaRuleTrainerSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement pDeltaRuleTrainerSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
IniLR = double.Parse(pDeltaRuleTrainerSettingsElem.Attribute("iniLR").Value, CultureInfo.InvariantCulture);
IncLR = double.Parse(pDeltaRuleTrainerSettingsElem.Attribute("incLR").Value, CultureInfo.InvariantCulture);
DecLR = double.Parse(pDeltaRuleTrainerSettingsElem.Attribute("decLR").Value, CultureInfo.InvariantCulture);
MinLR = double.Parse(pDeltaRuleTrainerSettingsElem.Attribute("minLR").Value, CultureInfo.InvariantCulture);
MaxLR = double.Parse(pDeltaRuleTrainerSettingsElem.Attribute("maxLR").Value, CultureInfo.InvariantCulture);
return;
}
/// <summary>
/// Creates an instance and initializes it from given xml element.
/// </summary>
/// <param name="elem">
/// Xml data containing SimpleIF activation settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public SimpleIFSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Activation.SimpleIFSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement activationSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
Resistance = RandomValueSettings.LoadOrDefault(activationSettingsElem, "resistance", TypicalResistance);
DecayRate = RandomValueSettings.LoadOrDefault(activationSettingsElem, "decayRate", TypicalDecayRate);
ResetV = RandomValueSettings.LoadOrDefault(activationSettingsElem, "resetV", TypicalResetV);
FiringThresholdV = RandomValueSettings.LoadOrDefault(activationSettingsElem, "firingThresholdV", TypicalFiringThresholdV);
RefractoryPeriods = int.Parse(activationSettingsElem.Attribute("refractoryPeriods").Value, CultureInfo.InvariantCulture);
return;
}
/// <summary>
/// Creates an instance and initializes it from given xml element.
/// </summary>
/// <param name="elem">
/// Xml data containing SimpleIF activation settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public SimpleIFSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Activation.SimpleIFSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement activationSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
StimuliCoeff = double.Parse(activationSettingsElem.Attribute("stimuliCoeff").Value, CultureInfo.InvariantCulture);
Resistance = new RandomValueSettings(activationSettingsElem.Descendants("resistance").FirstOrDefault());
DecayRate = new RandomValueSettings(activationSettingsElem.Descendants("decayRate").FirstOrDefault());
ResetV = new RandomValueSettings(activationSettingsElem.Descendants("resetV").FirstOrDefault());
FiringThresholdV = new RandomValueSettings(activationSettingsElem.Descendants("firingThresholdV").FirstOrDefault());
RefractoryPeriods = int.Parse(activationSettingsElem.Attribute("refractoryPeriods").Value, CultureInfo.InvariantCulture);
return;
}
/// <summary>
/// Creates the instance and initialize it from given xml element.
/// This is the preferred way to instantiate settings.
/// </summary>
/// <param name="elem">
/// Xml data containing settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public ParallelPerceptronSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Network.PP.ParallelPerceptronSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement settingsElem = validator.Validate(elem, "rootElem");
//Parsing
NumOfGates = int.Parse(settingsElem.Attribute("gates").Value, CultureInfo.InvariantCulture);
Resolution = int.Parse(settingsElem.Attribute("resolution").Value, CultureInfo.InvariantCulture);
OutputRange = new Interval(-1, 1);
XElement pDeltaRuleTrainerElem = settingsElem.Descendants("pDeltaRuleTrainer").First();
PDeltaRuleTrainerCfg = new PDeltaRuleTrainerSettings(pDeltaRuleTrainerElem);
return;
}
/// <summary>
/// Creates the instance and initialize it from given xml element.
/// </summary>
/// <param name="elem">
/// Xml data containing settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public InterconnectionSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Network.SM.Preprocessing.PoolInterconnectionSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement settingsElem = validator.Validate(elem, "rootElem");
//Parsing
//Density
Density = double.Parse(settingsElem.Attribute("density").Value, CultureInfo.InvariantCulture);
//Ratios
double relShareEE = double.Parse(settingsElem.Attribute("relShareEE").Value, CultureInfo.InvariantCulture);
double relShareEI = double.Parse(settingsElem.Attribute("relShareEI").Value, CultureInfo.InvariantCulture);
double relShareIE = double.Parse(settingsElem.Attribute("relShareIE").Value, CultureInfo.InvariantCulture);
double relShareII = double.Parse(settingsElem.Attribute("relShareII").Value, CultureInfo.InvariantCulture);
double sum = relShareEE + relShareEI + relShareIE + relShareII;
RatioEE = relShareEE / sum;
RatioEI = relShareEI / sum;
RatioIE = relShareIE / sum;
RatioII = relShareII / sum;
//Average distance
AvgDistance = settingsElem.Attribute("avgDistance").Value == "NA" ? 0d : double.Parse(settingsElem.Attribute("avgDistance").Value, CultureInfo.InvariantCulture);
//Allow self connections?
AllowSelfConnection = bool.Parse(settingsElem.Attribute("allowSelfConnection").Value);
//Will have each neuron the same number of connections?
ConstantNumOfConnections = bool.Parse(settingsElem.Attribute("constantNumOfConnections").Value);
//Synapse
XElement synapseCfgElem = settingsElem.Descendants().First();
if (synapseCfgElem.Name == "staticSynapse")
{
SynapseCfg = new StaticSynapseSettings(synapseCfgElem);
}
else
{
SynapseCfg = new DynamicSynapseSettings(synapseCfgElem);
}
return;
}
/// <summary>
/// Creates the instance and initializes it from given xml element.
/// Content of xml element is always validated against the xml schema.
/// </summary>
/// <param name="elem">Xml data containing resilient propagation trainer settings</param>
public RPropTrainerSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Network.FF.RPropTrainerSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement rPropTrainerSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
ZeroTolerance = double.Parse(rPropTrainerSettingsElem.Attribute("zeroTolerance").Value, CultureInfo.InvariantCulture);
PositiveEta = double.Parse(rPropTrainerSettingsElem.Attribute("positiveEta").Value, CultureInfo.InvariantCulture);
NegativeEta = double.Parse(rPropTrainerSettingsElem.Attribute("negativeEta").Value, CultureInfo.InvariantCulture);
IniDelta = double.Parse(rPropTrainerSettingsElem.Attribute("iniDelta").Value, CultureInfo.InvariantCulture);
MinDelta = double.Parse(rPropTrainerSettingsElem.Attribute("minDelta").Value, CultureInfo.InvariantCulture);
MaxDelta = double.Parse(rPropTrainerSettingsElem.Attribute("maxDelta").Value, CultureInfo.InvariantCulture);
return;
}
/// <summary>
/// Creates an instance and initializes it from given xml element.
/// </summary>
/// <param name="elem">
/// Xml data containing LeakyIF activation settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public LeakyIFSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Activation.LeakyIFSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement activationSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
TimeScale = RandomValueSettings.LoadOrDefault(activationSettingsElem, "timeScale", TypicalTimeScale);
Resistance = RandomValueSettings.LoadOrDefault(activationSettingsElem, "resistance", TypicalResistance);
RestV = RandomValueSettings.LoadOrDefault(activationSettingsElem, "restV", TypicalRestV);
ResetV = RandomValueSettings.LoadOrDefault(activationSettingsElem, "resetV", TypicalResetV);
FiringThresholdV = RandomValueSettings.LoadOrDefault(activationSettingsElem, "firingThresholdV", TypicalFiringThresholdV);
RefractoryPeriods = int.Parse(activationSettingsElem.Attribute("refractoryPeriods").Value, CultureInfo.InvariantCulture);
SolverMethod = ODENumSolver.ParseComputationMethodType(activationSettingsElem.Attribute("solverMethod").Value);
SolverCompSteps = int.Parse(activationSettingsElem.Attribute("solverCompSteps").Value, CultureInfo.InvariantCulture);
return;
}
/// <summary>
/// Creates the instance and initializes it from given xml element.
/// This is the preferred way to instantiate ReadoutLayer settings.
/// </summary>
/// <param name="elem">
/// Xml data containing ReadoutLayer settings.
/// Content of xml element is always validated against the xml schema.
/// </param>
public ReadoutLayerSettings(XElement elem)
{
//Validation
ElemValidator validator = new ElemValidator();
Assembly assemblyRCNet = Assembly.GetExecutingAssembly();
validator.AddXsdFromResources(assemblyRCNet, "RCNet.Neural.Network.SM.Readout.ReadoutLayerSettings.xsd");
validator.AddXsdFromResources(assemblyRCNet, "RCNet.RCNetTypes.xsd");
XElement readoutLayerSettingsElem = validator.Validate(elem, "rootElem");
//Parsing
TestDataRatio = double.Parse(readoutLayerSettingsElem.Attribute("testDataRatio").Value, CultureInfo.InvariantCulture);
NumOfFolds = readoutLayerSettingsElem.Attribute("folds").Value == "Auto" ? 0 : int.Parse(readoutLayerSettingsElem.Attribute("folds").Value);
//Readout units
ReadoutUnitCfgCollection = new List <ReadoutUnitSettings>();
foreach (XElement readoutUnitElem in readoutLayerSettingsElem.Descendants("readoutUnit"))
{
ReadoutUnitCfgCollection.Add(new ReadoutUnitSettings(readoutUnitElem));
}
return;
}
