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.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()); }
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()); }
private void Recalculate() { if (!CanRecalculate) return; var seriesVariables = new List<SeriesVariable>(); foreach (var selectedVariable in SelectedVariables) { seriesVariables.Add( new SeriesVariable( DataSeries.GetValues(_selectedEntities[0], selectedVariable.Name).ToArray(), DataSeries.GetValues(_selectedEntities[1], selectedVariable.Name).ToArray(), selectedVariable.Name, selectedVariable.Preprocessor, selectedVariable.Weight)); } var seriesVariablesArray = seriesVariables.ToArray(); var dtw = new Dtw( seriesVariablesArray, SelectedDistanceMeasure.Value, UseBoundaryConstraintStart, UseBoundaryConstraintEnd, UseSlopeConstraint ? SlopeConstraintDiagonal : (int?)null, UseSlopeConstraint ? SlopeConstraintAside : (int?)null, UseSakoeChibaMaxShift ? SakoeChibaMaxShift : (int?)null); if (MeasurePerformance) { var swDtwPerformance = new Stopwatch(); swDtwPerformance.Start(); for (int i = 0; i < 250; i++) { var tempDtw = new Dtw( seriesVariablesArray, SelectedDistanceMeasure.Value, UseBoundaryConstraintStart, UseBoundaryConstraintEnd, UseSlopeConstraint ? SlopeConstraintDiagonal : (int?)null, UseSlopeConstraint ? SlopeConstraintAside : (int?)null, UseSakoeChibaMaxShift ? SakoeChibaMaxShift : (int?)null); var tempDtwPath = tempDtw.GetCost(); } swDtwPerformance.Stop(); OperationDuration = swDtwPerformance.Elapsed; } Dtw = 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 }, // SelectedDistanceMeasure.Value, // UseBoundaryConstraintStart, // UseBoundaryConstraintEnd, // UseSlopeConstraint ? SlopeConstraintDiagonal : (int?)null, // UseSlopeConstraint ? SlopeConstraintAside : (int?)null, // UseSakoeChibaMaxShift ? SakoeChibaMaxShift : (int?)null); }
private void Recalculate() { if (!CanRecalculate) { return; } var seriesVariables = new List <SeriesVariable>(); foreach (var selectedVariable in SelectedVariables) { seriesVariables.Add( new SeriesVariable( DataSeries.GetValues(_selectedEntities[0], selectedVariable.Name).ToArray(), DataSeries.GetValues(_selectedEntities[1], selectedVariable.Name).ToArray(), selectedVariable.Name, selectedVariable.Preprocessor, selectedVariable.Weight)); } var seriesVariablesArray = seriesVariables.ToArray(); var dtw = new Dtw( seriesVariablesArray, SelectedDistanceMeasure.Value, UseBoundaryConstraintStart, UseBoundaryConstraintEnd, UseSlopeConstraint ? SlopeConstraintDiagonal : (int?)null, UseSlopeConstraint ? SlopeConstraintAside : (int?)null, UseSakoeChibaMaxShift ? SakoeChibaMaxShift : (int?)null); if (MeasurePerformance) { var swDtwPerformance = new Stopwatch(); swDtwPerformance.Start(); for (int i = 0; i < 250; i++) { var tempDtw = new Dtw( seriesVariablesArray, SelectedDistanceMeasure.Value, UseBoundaryConstraintStart, UseBoundaryConstraintEnd, UseSlopeConstraint ? SlopeConstraintDiagonal : (int?)null, UseSlopeConstraint ? SlopeConstraintAside : (int?)null, UseSakoeChibaMaxShift ? SakoeChibaMaxShift : (int?)null); var tempDtwPath = tempDtw.GetCost(); } swDtwPerformance.Stop(); OperationDuration = swDtwPerformance.Elapsed; } Dtw = 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 }, // SelectedDistanceMeasure.Value, // UseBoundaryConstraintStart, // UseBoundaryConstraintEnd, // UseSlopeConstraint ? SlopeConstraintDiagonal : (int?)null, // UseSlopeConstraint ? SlopeConstraintAside : (int?)null, // UseSakoeChibaMaxShift ? SakoeChibaMaxShift : (int?)null); }
public void OnDataChanged() { if (DrawCost && DrawDistance) { throw new Exception("Only one of the values can be drawn at once, 'cost' or 'distance'."); } double[][] matrixValues = null; if (DrawCost) { matrixValues = Dtw.GetCostMatrix(); } if (DrawDistance) { matrixValues = Dtw.GetDistanceMatrix(); } var dtwPath = Dtw.GetPath(); var xLength = Dtw.XLength; var yLength = Dtw.YLength; var cost = Dtw.GetCost(); var costNormalized = Dtw.GetCost() / Math.Sqrt(xLength * xLength + yLength * yLength); var plotModel = new PlotModel(String.Format("Dtw norm by length: {0:0.00}, total: {1:0.00}", costNormalized, cost)) { LegendTextColor = DrawCost || DrawDistance ? OxyColors.White : OxyColors.Black, }; if (matrixValues != null) { var maxMatrixValue = 0.0; for (int i = 0; i < xLength; i++) { for (int j = 0; j < yLength; j++) { maxMatrixValue = Math.Max(maxMatrixValue, Double.IsPositiveInfinity(matrixValues[i][j]) ? 0 : matrixValues[i][j]); } } for (int i = 0; i < xLength; i++) { for (int j = 0; j < yLength; j++) { var value = matrixValues[i][j]; var isValuePositiveInfinity = Double.IsPositiveInfinity(value); var intensityBytes = isValuePositiveInfinity ? new byte[] { 0, 0, 0 } : GetFauxColourRgbIntensity(value, 0, maxMatrixValue); //var intensityByte = (byte)(255 - Math.Floor(255 * intensity)); plotModel.Annotations.Add(new PolygonAnnotation { Points = new[] { new DataPoint(i - 0.5, j - 0.5), new DataPoint(i + 0.5, j - 0.5), new DataPoint(i + 0.5, j + 0.5), new DataPoint(i - 0.5, j + 0.5), }, StrokeThickness = 0, Selectable = false, Layer = AnnotationLayer.BelowAxes, Fill = OxyColor.FromArgb(255, intensityBytes[0], intensityBytes[1], intensityBytes[2]), }); } } for (int i = 0; i < 30; i++) { var intensityBytes = GetFauxColourRgbIntensity(i, 0, 29); plotModel.Annotations.Add(new RectangleAnnotation { MinimumX = -39, MaximumX = -25, MinimumY = -i - 6, MaximumY = -i - 5, Selectable = false, Fill = OxyColor.FromArgb(255, intensityBytes[0], intensityBytes[1], intensityBytes[2]) }); } plotModel.Annotations.Add(new TextAnnotation { Position = new DataPoint(-24, -5), HorizontalAlignment = HorizontalTextAlign.Left, VerticalAlignment = VerticalTextAlign.Middle, StrokeThickness = 0, Text = "0" }); plotModel.Annotations.Add(new TextAnnotation { Position = new DataPoint(-24, -34), HorizontalAlignment = HorizontalTextAlign.Left, VerticalAlignment = VerticalTextAlign.Middle, StrokeThickness = 0, Text = String.Format("{0:0.00}", maxMatrixValue), }); } var matrixPathSeries = new LineSeries("Path") { StrokeThickness = 1, Color = OxyColors.Red, }; for (int i = 0; i < dtwPath.Length; i++) { matrixPathSeries.Points.Add(new DataPoint(dtwPath[i].Item1, dtwPath[i].Item2)); } plotModel.Series.Add(matrixPathSeries); var seriesMatrixScale = (xLength + yLength) * 0.05; for (int variableIndex = 0; variableIndex < Dtw.SeriesVariables.Length; variableIndex++) { var variableA = Dtw.SeriesVariables[variableIndex]; var variableASeries = variableA.OriginalXSeries; var variableB = Dtw.SeriesVariables[variableIndex]; var variableBSeries = variableB.OriginalYSeries; var minSeriesA = variableASeries.Min(); var maxSeriesA = variableASeries.Max(); var normalizedSeriesA = variableASeries.Select(x => (x - minSeriesA) / (maxSeriesA - minSeriesA)).ToList(); var matrixSeriesA = new LineSeries(variableA.VariableName); for (int i = 0; i < normalizedSeriesA.Count; i++) { matrixSeriesA.Points.Add(new DataPoint(i, (-1 + normalizedSeriesA[i]) * seriesMatrixScale - 1 - seriesMatrixScale * (variableIndex + 1))); } plotModel.Series.Add(matrixSeriesA); var minSeriesB = variableBSeries.Min(); var maxSeriesB = variableBSeries.Max(); var normalizedSeriesB = variableBSeries.Select(x => (x - minSeriesB) / (maxSeriesB - minSeriesB)).ToList(); var matrixSeriesB = new LineSeries(variableB.VariableName); for (int i = 0; i < normalizedSeriesB.Count; i++) { matrixSeriesB.Points.Add(new DataPoint(-normalizedSeriesB[i] * seriesMatrixScale - 1 - seriesMatrixScale * (variableIndex + 1), i)); } plotModel.Series.Add(matrixSeriesB); } plotModel.Axes.Add(new LinearAxis(AxisPosition.Bottom, " Series A") { Maximum = Math.Max(xLength, yLength), PositionAtZeroCrossing = true }); plotModel.Axes.Add(new LinearAxis(AxisPosition.Left, " Series B") { Maximum = Math.Max(xLength, yLength), PositionAtZeroCrossing = true }); MatrixPlot.Model = plotModel; }
static void DTWCsv(string[] files) { for (int fileId = 0; fileId < files.Length; fileId++) { if (File.Exists(files[fileId].Split('\\').Last() + "_pearsonDataCsv.txt")) { File.Copy(files[fileId].Split('\\').Last() + "_pearsonDataCsv.txt", files[fileId] + "_pearsonDataCsv.txt", true); //Console.WriteLine("Copied " + files[fileId].Split('\\').Last() + "_pearsonDataCsv.txt" + " to " + files[fileId] + "_pearsonDataCsv.txt"); if (File.Exists(files[fileId].Split('\\').Last() + "dtwCostInfo.txt")) { File.Copy(files[fileId].Split('\\').Last() + "_pearsonDataCsv.txt", files[fileId] + "dtwCostInfo.txt", true); } Console.WriteLine(files[fileId].Split('\\').Last() + " is already done, skipping."); continue; } var freed = GC.GetTotalMemory(false); GC.Collect(GC.MaxGeneration, GCCollectionMode.Forced, true); Console.WriteLine("Garbage Collection completed - memory:" + ((double)GC.GetTotalMemory(false) / 1024 / 1024 / 1024).ToString("0.0") + " GB (freed " + (freed / 1024 / 1024) + " MB)"); Console.WriteLine("Performing DTW on csv data " + fileId + " of " + files.Length + ".."); var watch = System.Diagnostics.Stopwatch.StartNew(); string[] data = File.ReadAllLines(files[fileId]); Console.WriteLine("Data points: " + data.Length); List <double> testDataPoints = new List <double>(); List <double> recallDataPoints = new List <double>(); foreach (var line in data) { var split = line.Replace(',', '.').Split(';'); double test = double.Parse(split[0], System.Globalization.CultureInfo.InvariantCulture); double recall = double.Parse(split[1], System.Globalization.CultureInfo.InvariantCulture); testDataPoints.Add(test); recallDataPoints.Add(recall); } // Dtw dtw = new Dtw(testDataPoints.ToArray(), recallDataPoints.ToArray(), DistanceMeasure.Euclidean, true, true, null, null, 700); Dtw dtw = new Dtw(testDataPoints.ToArray(), recallDataPoints.ToArray(), DistanceMeasure.Euclidean, true, true, slopeStepSizeDiagonal: 2, slopeStepSizeAside: 1); var path = dtw.GetPath(); var cost = dtw.GetCost(); //var distanceMatrix = dtw.GetDistanceMatrix(); //var costMatrix = dtw.GetCostMatrix(); File.WriteAllText(files[fileId].Split('\\').Last() + "dtwCostInfo.txt", "cost=" + cost + "\nbefore_length=" + data.Length + "\nbefore_cost=" + (cost / data.Length) + "\nafter_length=" + path.Length + "\nafter_cost=" + (cost / path.Length) ); //PngExporter pngify = new PngExporter(); //pngify.Width = 36000; //pngify.Height = 4000; //var model = new PlotModel() { Title = "Red = test, blue = recall" }; //var aSeries = new OxyPlot.Series.LineSeries() { Color = OxyColors.Blue, MarkerSize = 10 }; //var bSeries = new OxyPlot.Series.LineSeries() { Color = OxyColors.Red, MarkerSize = 10 }; //for (int i = 0; i < testDataPoints.Count; i++) //{ // aSeries.Points.Add(new DataPoint(i, testDataPoints[i])); //} //for (int i = 0; i < recallDataPoints.Count; i++) //{ // bSeries.Points.Add(new DataPoint(i, recallDataPoints[i])); //} //List<string> pearsonData = new List<string>(); //foreach (var pairing in path) //{ // var lineSeries = new OxyPlot.Series.LineSeries() { Color = OxyColors.Gray, MarkerSize = 0.05 }; // lineSeries.Points.Add(new DataPoint(pairing.Item1, testDataPoints[pairing.Item1])); // lineSeries.Points.Add(new DataPoint(pairing.Item2, recallDataPoints[pairing.Item2])); // model.Series.Add(lineSeries); // pearsonData.Add(testDataPoints[pairing.Item1].ToString().Replace(',', '.') + ";" + recallDataPoints[pairing.Item2].ToString().Replace(',', '.')); //} //var pears = MathNet.Numerics.Statistics.Correlation.Pearson(path.Select(x => testDataPoints[x.Item1]).ToList(), path.Select(x => recallDataPoints[x.Item2]).ToList()); //Console.WriteLine("Pearson for " + files[fileId] + ":"); //Console.WriteLine(pears.ToString()); //File.WriteAllLines(files[fileId].Split('\\').Last() + "_pearsonDataCsv.txt", pearsonData); //model.Series.Add(aSeries); //model.Series.Add(bSeries); //pngify.ExportToFile(model, files[fileId].Split('\\').Last() + "_csv.png"); watch.Stop(); Console.WriteLine("Done in " + watch.Elapsed); Console.WriteLine(""); } }