#pragma warning disable 1998
public virtual async void ReceiveLogMessage(object sender, LogMessage message)
{
try
{
var match = _searchRegex.Match(message.Message);
if (!match.Success)
{
return;
}
if (int.TryParse(match.Groups[1].Value, out int power))
{
LastPower = power;
_movingStatistics.Push(power);
Notify();
}
else
{
_logger.LogWarning("{methodName} {message}", "ReceiveLogMessage", "Unable to parse calculated value " + match.Groups[0].Value);
}
}
catch (Exception e)
{
_logger.LogError(e, "{methodName} {message}", "ReceiveLogMessage", "unexpected error");
}
}
public void NegativeInfinityTest()
{
var ms = new MovingStatistics(3);
ms.Push(1.0);
ms.Push(2.0);
Assert.That(ms.Minimum, Is.Not.EqualTo(double.NegativeInfinity));
Assert.That(ms.Maximum, Is.Not.EqualTo(double.NegativeInfinity));
Assert.That(ms.Mean, Is.Not.EqualTo(double.NegativeInfinity));
Assert.That(ms.StandardDeviation, Is.Not.EqualTo(double.NegativeInfinity));
ms.Push(double.NegativeInfinity);
Assert.That(ms.Minimum, Is.EqualTo(double.NegativeInfinity));
Assert.That(ms.Maximum, Is.Not.EqualTo(double.NegativeInfinity));
Assert.That(ms.Mean, Is.EqualTo(double.NegativeInfinity));
Assert.That(ms.StandardDeviation, Is.NaN);
ms.Push(1.0);
Assert.That(ms.Minimum, Is.EqualTo(double.NegativeInfinity));
Assert.That(ms.Maximum, Is.Not.EqualTo(double.NegativeInfinity));
Assert.That(ms.Mean, Is.EqualTo(double.NegativeInfinity));
Assert.That(ms.StandardDeviation, Is.NaN);
ms.Push(double.NegativeInfinity);
Assert.That(ms.Minimum, Is.EqualTo(double.NegativeInfinity));
Assert.That(ms.Maximum, Is.Not.EqualTo(double.NegativeInfinity));
Assert.That(ms.Mean, Is.EqualTo(double.NegativeInfinity));
Assert.That(ms.StandardDeviation, Is.NaN);
ms.Push(2.0);
Assert.That(ms.Minimum, Is.EqualTo(double.NegativeInfinity));
Assert.That(ms.Maximum, Is.Not.EqualTo(double.NegativeInfinity));
Assert.That(ms.Mean, Is.EqualTo(double.NegativeInfinity));
Assert.That(ms.StandardDeviation, Is.NaN);
ms.Push(3.0);
Assert.That(ms.Minimum, Is.EqualTo(double.NegativeInfinity));
Assert.That(ms.Maximum, Is.Not.EqualTo(double.NegativeInfinity));
Assert.That(ms.Mean, Is.EqualTo(double.NegativeInfinity));
Assert.That(ms.StandardDeviation, Is.NaN);
ms.Push(4.0);
Assert.That(ms.Minimum, Is.Not.EqualTo(double.NegativeInfinity));
Assert.That(ms.Maximum, Is.Not.EqualTo(double.NegativeInfinity));
Assert.That(ms.Mean, Is.Not.EqualTo(double.NegativeInfinity));
Assert.That(ms.StandardDeviation, Is.Not.NaN);
}
public void NaNTest()
{
var ms = new MovingStatistics(3);
Assert.That(ms.Minimum, Is.NaN);
Assert.That(ms.Maximum, Is.NaN);
Assert.That(ms.Mean, Is.NaN);
Assert.That(ms.StandardDeviation, Is.NaN);
ms.Push(1.0);
Assert.That(ms.Minimum, Is.Not.NaN);
Assert.That(ms.Maximum, Is.Not.NaN);
Assert.That(ms.Mean, Is.Not.NaN);
Assert.That(ms.StandardDeviation, Is.NaN);
ms.Push(2.0);
Assert.That(ms.Minimum, Is.Not.NaN);
Assert.That(ms.Maximum, Is.Not.NaN);
Assert.That(ms.Mean, Is.Not.NaN);
Assert.That(ms.StandardDeviation, Is.Not.NaN);
ms.Push(double.NaN);
Assert.That(ms.Minimum, Is.NaN);
Assert.That(ms.Maximum, Is.NaN);
Assert.That(ms.Mean, Is.NaN);
Assert.That(ms.StandardDeviation, Is.NaN);
ms.Push(1.0);
Assert.That(ms.Minimum, Is.NaN);
Assert.That(ms.Maximum, Is.NaN);
Assert.That(ms.Mean, Is.NaN);
Assert.That(ms.StandardDeviation, Is.NaN);
ms.Push(2.0);
Assert.That(ms.Minimum, Is.NaN);
Assert.That(ms.Maximum, Is.NaN);
Assert.That(ms.Mean, Is.NaN);
Assert.That(ms.StandardDeviation, Is.NaN);
ms.Push(3.0);
Assert.That(ms.Minimum, Is.Not.NaN);
Assert.That(ms.Maximum, Is.Not.NaN);
Assert.That(ms.Mean, Is.Not.NaN);
Assert.That(ms.StandardDeviation, Is.Not.NaN);
}
public double UpdateEngagement(FaceAnchorReading f)
{
blink.Push((f.FacialExpressions["EyeBlinkLeft"].Value + f.FacialExpressions["EyeBlinkRight"].Value) / 2);
smile.Push((f.FacialExpressions["MouthSmileLeft"].Value + f.FacialExpressions["MouthSmileRight"].Value) / 2);
frown.Push((f.FacialExpressions["MouthFrownLeft"].Value + f.FacialExpressions["MouthFrownRight"].Value) / 2);
squint.Push((f.FacialExpressions["EyeSquintLeft"].Value + f.FacialExpressions["EyeSquintRight"].Value) / 2);
gazeIn.Push((f.FacialExpressions["EyeLookInLeft"].Value + f.FacialExpressions["EyeLookInRight"].Value) / 2);
gazeOut.Push((f.FacialExpressions["EyeLookOutLeft"].Value + f.FacialExpressions["EyeLookOutRight"].Value) / 2);
if (previousReading == null)
{
headSpeed.Push(0);
eyeDwell.Push(0);
headTilt.Push(0);
}
else
{
var deltaTime = f.ReadingTimestamp.Subtract(previousReading.ReadingTimestamp);
var deltaHead = VectorMagnitude(VectorDifference(previousReading.LookAtPointTransform, f.LookAtPointTransform));
headSpeed.Push((float)(deltaHead / deltaTime.TotalMilliseconds));
var leftEyeDisplacement = CoordinateDisplacement(f.LeftEyeTransform);
var rightEyeDisplacement = CoordinateDisplacement(f.RightEyeTransform);
var eyeDisplacement = Math.Abs(leftEyeDisplacement[0] + rightEyeDisplacement[0]) / 2;
eyeDwell.Push((float)(eyeDisplacement > 0 ? 1 / eyeDisplacement : 0));
headTilt.Push((float)(Math.Abs(leftEyeDisplacement[1] + rightEyeDisplacement[1]) / 2));
}
previousReading = f;
var modelInput = new CoreMLPathwayInput
{
PPI = PPI,
Blink = blink.Mean,
Smile = smile.Mean,
Frown = frown.Mean,
Squint = squint.Mean,
GazeIn = gazeIn.Mean,
GazeOut = gazeOut.Mean,
HeadSpeed = headSpeed.Mean,
EyeDwell = eyeDwell.Mean,
HeadTilt = headTilt.Mean
};
IMLFeatureProvider predictionOut = model.GetPrediction(modelInput, out _);
var targetFeatureValue = predictionOut.GetFeatureValue("target");
var prediction = targetFeatureValue.Int64Value;
var classProbabilityFeatureValue = predictionOut.GetFeatureValue("classProbability");
var probabilityx = classProbabilityFeatureValue.DictionaryValue.Values[0];
var probabilityy = classProbabilityFeatureValue.DictionaryValue.Values[1];
//// this is a bit hacky, but it's all relative
//value = (probabilityy.FloatValue - probabilityx.FloatValue - 0.5f) * 2f;
//value = (value < 0f) ? 0f : value;
value = probabilityy.FloatValue - probabilityx.FloatValue;
if (value < 0f)
{
Console.WriteLine(value + " negative !");
value = 0f;
}
else
{
Console.WriteLine(value);
}
return(value);
//return probabilityy.FloatValue;
//return prediction;
}
