public double Compare(PoseModel other)
{
NDtw.Dtw dtw;
double[][] firstSeries;
double[][] secondSeries;
double error = 0;
char[] components = { 'x', 'y', 'z', 'w' };
foreach (char component in components)
{
firstSeries = GetAllComponents(component);
secondSeries = other.GetAllComponents(component);
for (int i = 0; i < numberOfJoints; i++)
{
dtw = new NDtw.Dtw(firstSeries[i], secondSeries[i]);
error += dtw.GetCost();
}
}
return(error);
}
void waveSource_DataAvailable(object sender, WaveInEventArgs e)
{
//int max = 0;
byte[] buffer = e.Buffer;
int bytesRecorded = e.BytesRecorded;
//WriteToFile(buffer, bytesRecorded);
for (int index = 0; index < e.BytesRecorded; index += 2)
{
short sample = (short)((buffer[index + 1] << 8) |
buffer[index + 0]);
float sample32 = (sample / 32768f);
//int finalSample =(sample32 * 255);
//if (max < finalSample) max = finalSample;
//sampleAggregator.Add(sample32);
queue.Enqueue(sample32);
//queue.print();
}
long curTime = DateTime.Now.Ticks / TimeSpan.TicksPerSecond;
if (lastDetect + 2 > curTime)
{
Console.WriteLine("LAST GEST" + lastDetect + 5 + " " + curTime);
return;
}
//check if sample matches
int gest = 0;
double lastcost = 1000;
if (isSaved1 /*&& (loop++%3==0)*/){
long curTimeMs1 = DateTime.Now.Ticks / TimeSpan.TicksPerMillisecond; //Time Calc
var cost = new Dtw ( saved1 , queue.ToArray2()).GetCost();
long curTimeMs2 = DateTime.Now.Ticks / TimeSpan.TicksPerMillisecond; //Time Calc
if (cost < lastcost && cost < thresh1) { gest = 1; lastcost = cost; Console.WriteLine("G1: " + cost); }
//Debug.WriteLineIf( cost<thresh1, "1:"+cost);
Console.WriteLine("Time DTW Took for Gesture 1 in ms: " + ( curTimeMs2 - curTimeMs1));
//Console.WriteLine("MS 2: " + curTimeMs2);
}
if (isSaved2 /*&& (loop++%3==0)*/)
{
var cost = new Dtw(saved2, queue.ToArray2()).GetCost();
if (cost < lastcost && cost < thresh2)
{
gest = 2;
lastcost = cost;
Console.WriteLine("G2: " + cost);
}
//Debug.WriteLineIf(cost < thresh2, "2:"+cost);
}
if (isSaved3 /*&& (loop++%3==0)*/)
{
var cost = new Dtw(saved3, queue.ToArray2()).GetCost();
if (cost < lastcost && cost < thresh3) { gest = 3; lastcost = cost; Console.WriteLine("G3: "+cost); }
//Debug.WriteLineIf(cost < thresh3, "3:"+cost);
}
foreach (double[] s in falseSaved)
{
var cost = new Dtw(s, queue.ToArray2()).GetCost();
if (cost < lastcost && cost < thresh0) { gest = 0; lastcost = cost; }
}
thresh1 = Convert.ToDouble("0" + txtThres1.Text);
thresh2 = Convert.ToDouble("0"+txtThres2.Text );
thresh3 = Convert.ToDouble("0" + txtThres3.Text);
if (gest > 0)
{
lastDetect = DateTime.Now.Ticks / TimeSpan.TicksPerSecond;
lastGesture = gest;
Debug.WriteLine("DETECTED " + gest + " " + lastcost);
}
if (gest==1)
{
lbl1.Visible = true;
lbl2.Visible = false;
lbl3.Visible = false;
SerialForm.SendLeft();
ArrowForm.ShowLeft();
}
else if (gest==2)
{
lbl1.Visible = false;
lbl2.Visible = true;
lbl3.Visible = false;
SerialForm.SendCenter();
ArrowForm.ShowCenter();
}
else if(gest==3)
{
lbl1.Visible = false;
lbl2.Visible = false;
lbl3.Visible = true;
SerialForm.SendRight();
ArrowForm.ShowRight();
}
else
{
lbl1.Visible = false;
lbl2.Visible = false;
lbl3.Visible = false;
ArrowForm.ShowNone();
}
//else Debug.WriteLine("NONE");
//Debug.WriteLine(max.ToString());
}
public override double GetDistance(AudioFeature f, AudioFeature.DistanceType t)
{
if(!(f is Scms))
{
new Exception("Can only handle AudioFeatures of type Scms, not of: "+f);
return -1;
}
Scms other = (Scms)f;
DistanceMeasure distanceMeasure = DistanceMeasure.Euclidean;
switch (t) {
case AudioFeature.DistanceType.Dtw_Euclidean:
distanceMeasure = DistanceMeasure.Euclidean;
break;
case AudioFeature.DistanceType.Dtw_SquaredEuclidean:
distanceMeasure = DistanceMeasure.SquaredEuclidean;
break;
case AudioFeature.DistanceType.Dtw_Manhattan:
distanceMeasure = DistanceMeasure.Manhattan;
break;
case AudioFeature.DistanceType.Dtw_Maximum:
distanceMeasure = DistanceMeasure.Maximum;
break;
case AudioFeature.DistanceType.UCR_Dtw:
return UCRCSharp.UCR.DTW(this.GetArray(), other.GetArray());
case AudioFeature.DistanceType.CosineSimilarity:
return CosineSimilarity(this, other);
case AudioFeature.DistanceType.BitStringHamming:
return Imghash.ImagePHash.HammingDistance(this.BitString, other.BitString);
case AudioFeature.DistanceType.JaqSimilarity:
//return Soundfingerprinting.Hashing.MinHash.CalculateJaqSimilarity(this.Signature, other.Signature);
break;
case AudioFeature.DistanceType.KullbackLeiblerDivergence:
default:
return Distance(this, other, new ScmsConfiguration(Analyzer.MFCC_COEFFICIENTS));
}
Dtw dtw = new Dtw(this.GetArray(), other.GetArray(), distanceMeasure, true, true, null, null, null);
return dtw.GetCost();
}
public void SetData(Dtw dtw)
{
dtwGraph.Dtw = dtw;
}
/// <summary>
/// Generate average of supplied series.
/// </summary>
public static double[] Average(List<double[]> series, int maxIterations = 100)
{
if (series == null || series.Count == 0) throw new Exception("series null or empty");
if (series.Count == 1) return series[0];
if (series.Select(x => x.Length).Distinct().Count() != 1) throw new Exception("Series must be of equal length");
int length = series[0].Length;
//initializing the average to a simple mean of every point, without DTW
//double[] average = new double[length];
//for (int i = 0; i < series[0].Length; i++)
//{
// average[i] = series.Average(x => x[i]);
//}
//initialize to a random series from the input
//var r = new Random();
//double[] average = series[r.Next(0, series.Count - 1)];
//initialize to series closest to median min/max after detrending
List<double[]> tempSeries = series.Select(Detrend).ToList();
List<int> maxIndexes = tempSeries.Select(x => x.IndexOfMax()).ToList();
List<int> minIndexes = tempSeries.Select(x => x.IndexOfMin()).ToList();
double medianMaxIndex = maxIndexes.Median();
double medianMinIndex = minIndexes.Median();
var distances = maxIndexes.Select((x, i) => Math.Pow(x - medianMaxIndex, 2) + Math.Pow(minIndexes[i] - medianMinIndex, 2)).ToList();
int selectedSeries = distances.IndexOfMin();
double[] average = series[selectedSeries];
//this list will hold the values of each aligned point,
//later used to construct the aligned average
List<double>[] points = new List<double>[length];
for (int i = 0; i < length; i++)
{
points[i] = new List<double>();
}
double prevTotalDist = -1;
double totalDist = -2;
//sometimes the process gets "stuck" in a loop between two different states
//so we have to set a hard limit to end the loop
int count = 0;
//get the path between each series and the average
while (totalDist != prevTotalDist && count < maxIterations)
{
prevTotalDist = totalDist;
//clear the points from the last calculation
foreach (var list in points)
{
list.Clear();
}
//here we do the alignment for every series
foreach (double[] ts in series)
{
var dtw = new Dtw(new[] { new SeriesVariable(ts, average) });
Tuple<int, int>[] path = dtw.GetPath();
//use the path to distribute the points according to the warping
Array.ForEach(path, x => points[x.Item2].Add(ts[x.Item1]));
}
//Then simply construct the new average series by taking the mean of every List in points.
average = points.Select(x => x.Average()).ToArray();
//calculate Euclidean distance to stop the loop if no further improvement can be made
double[] average1 = average;
totalDist = series.Sum(x => x.Select((y, i) => Math.Pow(y - average1[i], 2)).Sum()); //we get convergence even though there's still work to be done
count++;
}
return average;
}
public static double DistanceFunc(IEnumerable<double> vector1, IEnumerable<double> vector2)
{
Dtw analyser = new Dtw(vector1.ToArray(), vector2.ToArray(), DistanceMeasure.SquaredEuclidean);
return analyser.GetCost();
}
private static void TestNDtw() {
bool UseBoundaryConstraintStart = true;
bool UseBoundaryConstraintEnd = true;
Dtw dtw = new Dtw(
new[] { 4.0, 4.0, 4.5, 4.5, 5.0, 5.0, 5.0, 4.5, 4.5, 4.0, 4.0, 3.5 },
new[] { 1.0, 1.5, 2.0, 2.5, 3.5, 4.0, 3.0, 2.5, 2.0, 2.0, 2.0, 1.5 },
DistanceMeasure.Euclidean,
UseBoundaryConstraintStart,
UseBoundaryConstraintEnd,
null,
null,
null);
double cost = dtw.GetCost();
Console.Out.WriteLine(String.Format("DTW: {0}", cost));
System.Console.ReadLine();
return;
}
private double CalculateCost(SignModel sm1, SignModel sm2)
{
var seriesVariables = new List<SeriesVariable>();
seriesVariables.Add(
new SeriesVariable(
sm1.H_horizantal.ToArray(),
sm2.H_horizantal.ToArray()));
seriesVariables.Add(
new SeriesVariable(
sm1.H_vertical.ToArray(),
sm2.H_vertical.ToArray()));
var seriesVariablesArray = seriesVariables.ToArray();
var dtw = new Dtw(seriesVariablesArray);
m_dtw = dtw;
return dtw.GetCost();
}
/// <summary>Get Distance</summary>
/// <seealso cref="">comirva.audio.feature.AudioFeature#GetDistance(comirva.audio.feature.AudioFeature)</seealso>
public override double GetDistance(AudioFeature f, AudioFeature.DistanceType t)
{
if(!(f is MandelEllis))
{
new Exception("Can only handle AudioFeatures of type Mandel Ellis, not of: "+f);
return -1;
}
MandelEllis other = (MandelEllis)f;
DistanceMeasure distanceMeasure = DistanceMeasure.Euclidean;
switch (t) {
case AudioFeature.DistanceType.Dtw_Euclidean:
distanceMeasure = DistanceMeasure.Euclidean;
break;
case AudioFeature.DistanceType.Dtw_SquaredEuclidean:
distanceMeasure = DistanceMeasure.SquaredEuclidean;
break;
case AudioFeature.DistanceType.Dtw_Manhattan:
distanceMeasure = DistanceMeasure.Manhattan;
break;
case AudioFeature.DistanceType.Dtw_Maximum:
distanceMeasure = DistanceMeasure.Maximum;
break;
case AudioFeature.DistanceType.KullbackLeiblerDivergence:
default:
return KullbackLeibler(this.gmmMe, other.gmmMe) + KullbackLeibler(other.gmmMe, this.gmmMe);
}
Dtw dtw = new Dtw(this.GetArray(), other.GetArray(), distanceMeasure, true, true, null, null, null);
return dtw.GetCost();
}
