public void WhenDiscriminabilityValueIsNeeded()
{
_foveaPeripheryOperatingCharacteristic = new Mock<NormalDistribution>();
const int fixation = 1;
const int location = 4;
_distanceFromFixation = Math.Abs(fixation - location) - 1;
var fpoc = new ObservationGenerationModel(_foveaPeripheryOperatingCharacteristic.Object,
fixation, location);
fpoc.GenerateDiscriminabilityValue();
}
public double[] CalculateState(double[] activation, int fixation)
{
for (var i = 0; i < activation.Length; i++)
{
//discriminability is explained in Butko and Movellan (2008) and is determined using FPOC and eccentricity from fixation.
var discriminability =
new ObservationGenerationModel(_foveaPeripheryOperatingCharacteristic, fixation, i)
.GenerateDiscriminabilityValue();
//This is equation 6 in the Butko & Movellan (2008) paper determining belief state
State[i] = State[i]*Math.Exp(activation[i]*discriminability);
}
return State;
}
public double[] CalculateState(double[] activation, int fixation)
{
++_numberOfFixation;
for (var i = 0; i < activation.Length; i++)
{
var discriminability =
new ObservationGenerationModel(_foveaPeripheryOperatingCharacteristic, fixation, i)
.GenerateDiscriminabilityValue();
State[i] = State[i]*Math.Exp(activation[i]*discriminability);
}
_beliefStateDataRecorder.Insert(_numberOfFixation, (double[]) State.Clone());
return State;
}
public bool Update(double[] activation, int fixation)
{
++ _numberOfFixation;
for (var i = 0; i < activation.Length; i++)
{
//discriminability is explained in Butko and Movellan (2008) and is determined using FPOC and eceentricity from fixation.
var discriminability =
new ObservationGenerationModel(_foveaPeripheryOperatingCharacteristic, fixation, i)
.GenerateDiscriminabilityValue();
State[i] = State[i]*Math.Exp(activation[i]*discriminability); //This is equation 6 in the Butko & Movellan (2008) paper determining belief state
}
_beliefStateDataRecorder.Insert(_numberOfFixation, (double[]) State.Clone());//Stores belief states for output onto graph
return State.Any(s => s >= 0.9);
}
public double[] GenerateActivation(int fixation, int[] visualArray)
{
var activationValues = new double[visualArray.Length];
_observationValues = GenerateObservations(fixation, visualArray);
for (var i = 0; i < visualArray.Length; i++)
{
//discriminability is explained in Butko and Movellan (2008) and is determined using FPOC and eceentricity from fixation.
var discriminability =
new ObservationGenerationModel(_standardDistribution, fixation, i)
.GenerateDiscriminabilityValue();
activationValues[i] = _observationValues[i] - discriminability/2;
}
return activationValues;
}
private double[] GenerateObservations(int fixation, int[] visualArray)
{
_observationValues = new double[visualArray.Length];
for (var location = 0; location < visualArray.Length; location++)
{
if (visualArray[location] == 0)
{
_observationValues[location] = _standardDistribution.Generate();
}
else
{
//discriminability is explained in Butko and Movellan (2008) and is determined using FPOC and eceentricity from fixation.
var discriminability =
new ObservationGenerationModel(_standardDistribution, fixation, location)
.GenerateDiscriminabilityValue();
_observationValues[location] = new NormalDistribution(discriminability, 1.0).Generate();
}
}
return _observationValues;
}