public FittsTrial(FittsTime _time, FittsCoordinate _coord, bool isTouchingTarget, FittsTrajectory _trajectory)
{
time = _time;
coord = _coord;
trajectory = _trajectory;
isError = !isTouchingTarget;
}
public bool AddTriggerEvent(Vector3 pos, FittsTime time, bool trialIsError)
{
// Check if first selection because it is not recorded
if (!TargetsCreator.IsFirstTarget())
{
AddTrial(pos, time, trialIsError);
}
// Start a new trajectory for the new target because each trial has his trajectory
trajectory = new FittsTrajectory();
return(parameter.nbOfTarget == fittsTrials.Count);
}
public SequenceStatistic(FittsSequence _sequence)
{
trialsStats = new List <TrialStatistic>();
sequence = _sequence;
foreach (FittsTrial trial in sequence.fittsTrials)
{
trialsStats.Add(new TrialStatistic(trial));
}
// We
effectiveWidth = 4.133 * CalculateStandardDeviation(new List <double>(trialsStats.Select(x => x.dx)));
// Ae (mean)
effectiveAmplitudeMean = trialsStats.Sum(x => x.effectiveAmplitude) / trialsStats.Count;
// IDe
effectiveIndexDifficulty = Math.Log((effectiveAmplitudeMean / effectiveWidth) + 1, 2);
// TP
throughput = effectiveIndexDifficulty / (sequence.fittsTrials.Sum(x => x.time.movementTime) / sequence.fittsTrials.Count);
// MT
timeMean = new FittsTime(sequence.fittsTrials.Sum(x => x.time.pointingTime) / sequence.fittsTrials.Count, sequence.fittsTrials.Sum(x => x.time.selectionTime) / sequence.fittsTrials.Count);
// ER(%)
errorMean = (double)sequence.fittsTrials.Where(x => x.isError).Count() / (double)sequence.fittsTrials.Count;
errorMean *= 100;
// Eye Data
eyeData = TargetsCreator.GetEyeData();
}
private void AddTrial(Vector3 pos, FittsTime time, bool trialIsError)
{
FittsCoordinate coord = new FittsCoordinate(TargetsCreator.GetLastTargetPosition(), TargetsCreator.GetCurrentTargetPosition(), new Vector2(pos.x, pos.y));
fittsTrials.Add(new FittsTrial(time, coord, trialIsError, trajectory));
}
