//Constructor
/// <summary>
/// Creates an initialized instance
/// </summary>
/// <param name="settings">Configuration</param>
/// <param name="seek">
/// Initial seek of the random generator.
/// Specify seek less than 0 to obtain different initialization each time Reset is invoked.
/// </param>
public RandomGenerator(RandomValueSettings settings, int seek = 0)
{
_settings = settings.DeepClone();
_seek = seek;
Reset();
return;
}
//Constructor
/// <summary>
/// Creates an initialized instance.
/// </summary>
/// <param name="cfg">The RandomValue configuration.</param>
/// <param name="seek">The initial seek of the random generator. Specify the seek less than 0 to obtain different initialization each time the Reset is invoked.</param>
public RandomGenerator(RandomValueSettings cfg, int seek = 0)
{
_cfg = (RandomValueSettings)cfg.DeepClone();
_seek = seek;
Reset();
return;
}
//Constructors
/// <summary>
/// Creates an initialized instance
/// </summary>
/// <param name="stimuliCoeff">Input stimuli coefficient (pA)</param>
/// <param name="timeScale">Membrane time scale (ms)</param>
/// <param name="resistance">Membrane resistance (Mohm)</param>
/// <param name="restV">Membrane rest potential (mV)</param>
/// <param name="resetV">Membrane reset potential (mV)</param>
/// <param name="rheobaseV">Membrane rheobase threshold (mV)</param>
/// <param name="firingThresholdV">Membrane firing threshold (mV)</param>
/// <param name="sharpnessDeltaT">Sharpness of membrane potential change (mV)</param>
/// <param name="refractoryPeriods">Number of after spike computation cycles while an input stimuli is ignored (ms)</param>
/// <param name="solverMethod">ODE numerical solver method</param>
/// <param name="solverCompSteps">ODE numerical solver computation steps of the time step</param>
public ExpIFSettings(double stimuliCoeff,
RandomValueSettings timeScale,
RandomValueSettings resistance,
RandomValueSettings restV,
RandomValueSettings resetV,
RandomValueSettings rheobaseV,
RandomValueSettings firingThresholdV,
RandomValueSettings sharpnessDeltaT,
int refractoryPeriods,
ODENumSolver.Method solverMethod,
int solverCompSteps
)
{
StimuliCoeff = stimuliCoeff;
TimeScale = timeScale.DeepClone();
Resistance = resistance.DeepClone();
RestV = restV.DeepClone();
ResetV = resetV.DeepClone();
RheobaseV = rheobaseV.DeepClone();
FiringThresholdV = firingThresholdV.DeepClone();
SharpnessDeltaT = sharpnessDeltaT.DeepClone();
RefractoryPeriods = refractoryPeriods;
SolverMethod = solverMethod;
SolverCompSteps = solverCompSteps;
return;
}
//Constructors
/// <summary>
/// Creates an initialized instance
/// </summary>
/// <param name="stimuliCoeff">Input stimuli coefficient (pA)</param>
/// <param name="timeScale">Membrane time scale (ms)</param>
/// <param name="resistance">Membrane resistance (Mohm)</param>
/// <param name="restV">Membrane rest potential (mV)</param>
/// <param name="resetV">Membrane reset potential (mV)</param>
/// <param name="rheobaseV">Membrane rheobase threshold (mV)</param>
/// <param name="firingThresholdV">Membrane firing threshold (mV)</param>
/// <param name="sharpnessDeltaT">Sharpness of membrane potential change (mV)</param>
/// <param name="adaptationVoltageCoupling">Adaptation voltage coupling (nS)</param>
/// <param name="adaptationTimeConstant">Adaptation time constant (ms)</param>
/// <param name="adaptationSpikeTriggeredIncrement">Spike triggered adaptation increment (pA)</param>
/// <param name="solverMethod">ODE numerical solver method</param>
/// <param name="solverCompSteps">ODE numerical solver computation steps of the time step</param>
public AdExpIFSettings(double stimuliCoeff,
RandomValueSettings timeScale,
RandomValueSettings resistance,
RandomValueSettings restV,
RandomValueSettings resetV,
RandomValueSettings rheobaseV,
RandomValueSettings firingThresholdV,
RandomValueSettings sharpnessDeltaT,
RandomValueSettings adaptationVoltageCoupling,
RandomValueSettings adaptationTimeConstant,
RandomValueSettings adaptationSpikeTriggeredIncrement,
ODENumSolver.Method solverMethod,
int solverCompSteps
)
{
StimuliCoeff = stimuliCoeff;
TimeScale = timeScale.DeepClone();
Resistance = resistance.DeepClone();
RestV = restV.DeepClone();
ResetV = resetV.DeepClone();
RheobaseV = rheobaseV.DeepClone();
FiringThresholdV = firingThresholdV.DeepClone();
SharpnessDeltaT = sharpnessDeltaT.DeepClone();
AdaptationVoltageCoupling = adaptationVoltageCoupling.DeepClone();
AdaptationTimeConstant = adaptationTimeConstant.DeepClone();
AdaptationSpikeTriggeredIncrement = adaptationSpikeTriggeredIncrement.DeepClone();
SolverMethod = solverMethod;
SolverCompSteps = solverCompSteps;
return;
}
/// <summary>
/// Creates initialized instance
/// </summary>
/// <param name="restingEfficacy">Synapse's resting efficacy (average probability of neurotransmitter release)</param>
/// <param name="tauDepression">Synapse's efficacy depression model time constant (ms)</param>
/// <param name="tauFacilitation">Synapse's efficacy facilitation model time constant (ms)</param>
/// <param name="applyShortTermPlasticity">Specifies whether to apply short-term plasticity</param>
/// <param name="weightCfg">Synapse's random weight settings</param>
public DynamicsSettings(double restingEfficacy,
double tauDepression,
double tauFacilitation,
bool applyShortTermPlasticity,
RandomValueSettings weightCfg = null
)
{
RestingEfficacy = restingEfficacy;
TauDepression = tauDepression;
TauFacilitation = tauFacilitation;
ApplyShortTermPlasticity = applyShortTermPlasticity;
WeightCfg = (weightCfg == null ? new RandomValueSettings(0, 1) : weightCfg.DeepClone());
return;
}
//Constructors
/// <summary>
/// Creates an initialized instance
/// </summary>
/// <param name="stimuliCoeff">Initial input stimuli coefficient (pA)</param>
/// <param name="resistance">Membrane resistance (Mohm)</param>
/// <param name="decayRate">Membrane potential decay rate</param>
/// <param name="resetV">Membrane reset potential (mV)</param>
/// <param name="firingThresholdV">Membrane firing threshold (mV)</param>
/// <param name="refractoryPeriods">Number of after spike computation cycles while an input stimuli is ignored (ms)</param>
public SimpleIFSettings(double stimuliCoeff,
RandomValueSettings resistance,
RandomValueSettings decayRate,
RandomValueSettings resetV,
RandomValueSettings firingThresholdV,
int refractoryPeriods
)
{
StimuliCoeff = stimuliCoeff;
Resistance = resistance.DeepClone();
DecayRate = decayRate.DeepClone();
ResetV = resetV.DeepClone();
FiringThresholdV = firingThresholdV.DeepClone();
RefractoryPeriods = refractoryPeriods;
return;
}
//Constructors
/// <summary>
/// Creates an initialized instance.
/// </summary>
/// <param name="name">The name of the neuron group.</param>
/// <param name="relShare">Specifies how big relative portion of pool's neurons is formed by this group of the neurons.</param>
/// <param name="activationCfg">The common configuration of the neurons' activation function.</param>
/// <param name="predictorsCfg">The common configuration of the predictors provider.</param>
/// <param name="firingThreshold">The firing threshold value. Every time the current normalized activation is higher than the normalized past reference activation by at least this threshold, it is evaluated as a firing event.</param>
/// <param name="thresholdMaxRefDeepness">Maximum age of the past activation for the evaluation of the firing event.</param>
/// <param name="biasCfg">The configuration of the constant input bias.</param>
/// <param name="retainmentCfg">The configuration of the neurons' retainment property.</param>
public AnalogNeuronGroupSettings(string name,
double relShare,
IActivationSettings activationCfg,
PredictorsProviderSettings predictorsCfg,
double firingThreshold = DefaultFiringThreshold,
int thresholdMaxRefDeepness = DefaultThresholdMaxRefDeepness,
RandomValueSettings biasCfg = null,
RetainmentSettings retainmentCfg = null
)
{
Name = name;
RelShare = relShare;
ActivationCfg = (IActivationSettings)activationCfg.DeepClone();
PredictorsCfg = (PredictorsProviderSettings)predictorsCfg.DeepClone();
FiringThreshold = firingThreshold;
ThresholdMaxRefDeepness = thresholdMaxRefDeepness;
BiasCfg = biasCfg == null ? null : (RandomValueSettings)biasCfg.DeepClone();
RetainmentCfg = retainmentCfg == null ? null : (RetainmentSettings)retainmentCfg.DeepClone();
Check();
return;
}
//Constructors
/// <summary>
/// Creates an initialized instance
/// </summary>
/// <param name="stimuliCoeff">Input stimuli coefficient (pA)</param>
/// <param name="recoveryTimeScale">Time scale of the recovery variable</param>
/// <param name="recoverySensitivity">Sensitivity of the recovery variable to the subthreshold fluctuations of the membrane potential</param>
/// <param name="recoveryReset">After-spike reset of the recovery variable</param>
/// <param name="restV">Membrane rest potential (mV)</param>
/// <param name="resetV">Membrane reset potential (mV)</param>
/// <param name="firingThresholdV">Membrane firing threshold (mV)</param>
/// <param name="refractoryPeriods">Number of after spike computation cycles while an input stimuli is ignored (ms)</param>
/// <param name="solverMethod">ODE numerical solver method</param>
/// <param name="solverCompSteps">ODE numerical solver computation steps of the time step</param>
public IzhikevichIFSettings(double stimuliCoeff,
RandomValueSettings recoveryTimeScale,
RandomValueSettings recoverySensitivity,
RandomValueSettings recoveryReset,
RandomValueSettings restV,
RandomValueSettings resetV,
RandomValueSettings firingThresholdV,
int refractoryPeriods,
ODENumSolver.Method solverMethod,
int solverCompSteps
)
{
StimuliCoeff = stimuliCoeff;
RecoveryTimeScale = recoveryTimeScale.DeepClone();
RecoverySensitivity = recoverySensitivity.DeepClone();
RecoveryReset = recoveryReset.DeepClone();
RestV = restV.DeepClone();
ResetV = resetV.DeepClone();
FiringThresholdV = firingThresholdV.DeepClone();
RefractoryPeriods = refractoryPeriods;
SolverMethod = solverMethod;
SolverCompSteps = solverCompSteps;
return;
}
//Constructors
/// <summary>
/// Creates an initialized instance
/// </summary>
/// <param name="alpha">The Alpha</param>
public ISRUSettings(RandomValueSettings alpha)
{
Alpha = alpha.DeepClone();
return;
}
//Constructors
/// <summary>
/// Creates an initialized instance
/// </summary>
/// <param name="negSlope">The negative slope</param>
public LeakyReLUSettings(RandomValueSettings negSlope)
{
NegSlope = negSlope.DeepClone();
return;
}
//Constructors
/// <summary>
/// Creates an initialized instance
/// </summary>
/// <param name="name">Name of the neuron group</param>
/// <param name="relShare">Specifies how big relative portion of pool's neurons is formed by this group of the neurons</param>
/// <param name="activationCfg">Common activation function settings of the groupped neurons</param>
/// <param name="homogenousExcitabilityCfg">Configuration of the neuron's homogenous excitability</param>
/// <param name="biasCfg">Each neuron within the group receives constant input bias. Value of the neuron's bias is driven by this random settings</param>
/// <param name="predictorsCfg">Configuration of the predictors</param>
public SpikingNeuronGroupSettings(string name,
double relShare,
RCNetBaseSettings activationCfg,
HomogenousExcitabilitySettings homogenousExcitabilityCfg = null,
RandomValueSettings biasCfg = null,
PredictorsSettings predictorsCfg = null
)
{
Name = name;
RelShare = relShare;
ActivationCfg = activationCfg.DeepClone();
HomogenousExcitabilityCfg = homogenousExcitabilityCfg == null ? new HomogenousExcitabilitySettings() : (HomogenousExcitabilitySettings)homogenousExcitabilityCfg.DeepClone();
BiasCfg = biasCfg == null ? null : (RandomValueSettings)biasCfg.DeepClone();
PredictorsCfg = predictorsCfg == null ? null : (PredictorsSettings)predictorsCfg.DeepClone();
Check();
return;
}
//Constructors
/// <summary>
/// Creates an initialized instance
/// </summary>
/// <param name="alpha">The Alpha</param>
public SoftExponentialSettings(RandomValueSettings alpha)
{
Alpha = alpha.DeepClone();
return;
}
//Constructors
/// <summary>
/// Creates an initialized instance
/// </summary>
/// <param name="slope">Slope of the curve</param>
public ElliotSettings(RandomValueSettings slope)
{
Slope = slope.DeepClone();
return;
}
