// Update is called once per frame
void Update()
{
//displayText2.text="Filtering is : " + filter +" labels are : ";//+ts.GetNbOfLabels() + "\t label is :" + ts.GetLabels().Length;
displayText.text = " Labesl are : " + ts.GetNbOfLabels() + "\t labels are \t " + labelstoString(ts) + "\t" + "\t Likeliest is " + hhmm.GetLikeliest() + " filter is " + filter; // ts.GetLabels().Length;
//displayText2.text = " Likelihood is: " + gyroDelta[0] + "\t"+ gyroDelta[1] +"\t" + gyroDelta[2] ; //+"\t"+ hhmm.GetLikelihoods()[0] + "\t"+ hhmm.GetLikelihoods()[1] + "\t" + hhmm.GetLikeliest();
displayText.text = "";
displayText2.text = "";
if (hhmm.GetTimeProgressions()[1] > 0.95f && hhmm.GetTimeProgressions()[1] < 1.05f)
{
//filter = false;
goLevelDesign.GetComponent <LevelDesignWords>().letter = ts.GetLabels()[1];
//displayText3.text = "after clear()" + hhmm.GetTimeProgressions()[1] ;
}
else
{
displayText3.text = " ";
//filter = true;
}
if (filter)
{
gyroDistanceThreshold = thresholds[dataStreamer.modeValue]; //threshold as a function of the recording mode
gyroCoords[0] = dataStreamer.data[0];
gyroCoords[1] = dataStreamer.data[1];
gyroCoords[2] = dataStreamer.data[2];
if (distance(gyroCoords, prevGyroCoords) > gyroDistanceThreshold)
{
//not over the threshold
displayText2.text = " Likelihood is: " + "\t" + likelihoodsString(ts); //+ distance(gyroCoords, prevGyroCoords) + "\t" + gyroCoords[0]+ "\t"+ prevGyroCoords[0] + "\t" + gyroDistanceThreshold;
/*+ hhmm.GetTimeProgressions()[0] + "\t" + hhmm.GetTimeProgressions()[1] */
hhmm.Filter(gyroDelta);
likeliest = hhmm.GetLikeliest();
likelihoods = hhmm.GetLikelihoods();
prevGyroCoords[0] = gyroCoords[0]; //dataStreamer.data[0];
prevGyroCoords[1] = gyroCoords[1]; //dataStreamer.data[1];
prevGyroCoords[2] = gyroCoords[2]; //dataStreamer.data[2];
}
else //filter if there s a motion
{
displayText3.text = "Please move ! ";
}
}
else
{
displayText3.text = " ";
//displayText3.text = " Not Filtering ! ";
//goLevelDesign.GetComponent<LevelDesignWords>().letter = "" ;
}
}
private string labelstoString(XmmTrainingSet ts)
{
string s = "";
for (int i = 0; i < ts.GetLabels().Length; i++)
{
s += ts.GetLabels()[i] + "\t";
}
return(s);
}
private void logLabels()
{
string[] labels = ts.GetLabels();
Debug.Log("nb of labels : " + labels.Length);
for (int i = 0; i < labels.Length; ++i)
{
Debug.Log("label " + i + " : " + labels[i]);
}
}
private string likelihoodsString(XmmTrainingSet ts)
{
string s = "";
for (int i = 0; i < ts.GetLabels().Length; i++)
{
s += hhmm.GetTimeProgressions()[i] + "\t";
}
return(s);
}