private void sensorDataProcessor(SignalClassifierController classifier, int sensorQty,
ref IEnumerable <IEnumerable <short> > readings, string robotBodyPart)
{
var frame = readings;
var processingResult = predictSingleFrame(frame, classifier, sensorQty);
Console.WriteLine(processingResult);
var eventArgs = new DataProcessorEventArgs();
if (processingResult.classPercentages.All(cp => cp < 0.6) &&
!processingResult.prediction.Contains("Strike"))
{
switch (robotBodyPart)
{
case "topHead":
eventArgs.predictionData = "OtherLowTopHead";
break;
case "leftSideHead":
eventArgs.predictionData = "OtherLowLeftSideHead";
break;
case "rightSideHead":
eventArgs.predictionData = "OtherLowRightSideHead";
break;
case "rightHand":
eventArgs.predictionData = "OtherLowRightHand";
break;
case "leftHand":
eventArgs.predictionData = "OtherLowLeftHand";
break;
case "front":
eventArgs.predictionData = "OtherLowFront";
break;
default:
eventArgs.predictionData = "OtherLowLeftSideHead";
break;
}
}
else
{
eventArgs.predictionData = processingResult.prediction;
}
sensorDataProcessed.Invoke(this, eventArgs);
eventArgs = null;
readings = Enumerable.Repeat(Enumerable.Repeat <short>(0, sensorQty), 100);
}
private SignalClassifierController.PredictionResult predictFrame(
IEnumerable <IEnumerable <short> > frame, int frameSize, SignalClassifierController classifier, int sensorQty)
{
var adjustedFrame =
Enumerable.Repeat(Enumerable.Repeat <short>(0, sensorQty), frameSize).ToArray();
var frameArray = frame.ToArray();
for (int i = 0; i < (frameArray.Length > frameSize ? adjustedFrame.Length : frameArray.Length); i++)
{
adjustedFrame[i] = frameArray[i];
}
string strFrameSize = "";
if (frameSize == 100)
{
strFrameSize = "single";
}
else if (frameSize == 200)
{
strFrameSize = "double";
}
else
{
strFrameSize = "half";
}
string sensorType = "";
if (sensorQty == 4)
{
sensorType = "four";
}
else
{
sensorType = "two";
}
return(classifier.predict(strFrameSize, sensorType, classifier.convertFrame(adjustedFrame)));
}
private SignalClassifierController.PredictionResult predictDoubleFrame(
IEnumerable <IEnumerable <short> > frame, SignalClassifierController classifier, int sensorQty)
{
return(predictFrame(frame, 200, classifier, sensorQty));
}
