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https://github.com/vale981/VoiDPlugins
synced 2025-03-05 09:11:38 -05:00
[ExpASFilter] Simplify the configuration
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X9VoiD
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1 changed files with 38 additions and 69 deletions
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@ -1,6 +1,5 @@
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using ExpASFilter;
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using MathNet.Numerics;
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using MathNet.Numerics.LinearRegression;
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using System;
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using System.Collections.Generic;
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using TabletDriverPlugin;
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@ -17,7 +16,6 @@ namespace OpenTabletDriverPlugins
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{
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DateTime date = DateTime.Now;
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CalcReportRate(date);
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var reportRateAvg = CalcReportRateAvg();
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if (AddTimeSeriesPoint(point, date))
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{
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@ -36,23 +34,12 @@ namespace OpenTabletDriverPlugins
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}
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Polynomial xCoeff, yCoeff;
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if (Weighted)
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{
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var weights = CalcWeight();
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xCoeff = new Polynomial(Fit.PolynomialWeighted(timeMatrix, x, weights, Degree));
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yCoeff = new Polynomial(Fit.PolynomialWeighted(timeMatrix, y, weights, Degree));
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}
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else
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{
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xCoeff = new Polynomial(Fit.Polynomial(timeMatrix, x, Degree, DirectRegressionMethod.Svd));
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yCoeff = new Polynomial(Fit.Polynomial(timeMatrix, y, Degree, DirectRegressionMethod.Svd));
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}
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var weights = CalcWeight(Weight);
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xCoeff = new Polynomial(Fit.PolynomialWeighted(timeMatrix, x, weights, Degree));
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yCoeff = new Polynomial(Fit.PolynomialWeighted(timeMatrix, y, weights, Degree));
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double predictAhead;
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if (Sync)
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predictAhead = 1000.0 / reportRateAvg * Ahead;
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else
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predictAhead = (date - _timeSeriesPoints.First.Value.Date).TotalMilliseconds + Compensation;
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predictAhead = (date - _timeSeriesPoints.First.Value.Date).TotalMilliseconds + Compensation;
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predicted.X = (float)xCoeff.Evaluate(predictAhead);
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predicted.Y = (float)yCoeff.Evaluate(predictAhead);
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@ -64,7 +51,7 @@ namespace OpenTabletDriverPlugins
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var now = DateTime.Now;
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if ((now - date).TotalMilliseconds > CalcReportRateAvg())
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Log.Write("ExpASFilter", now + ": CPU choking hard. Latency higher than normal. We missed a hz.");
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Log.Write("ExpASFilter", now + ": High CPU Latency. Report delayed.");
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_lastTime = date;
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return predicted;
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@ -107,15 +94,11 @@ namespace OpenTabletDriverPlugins
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if (axis == Axis.X)
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foreach (var timePoint in _timeSeriesPoints)
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{
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points[++index] = timePoint.Point.X;
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}
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else if (axis == Axis.Y)
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foreach (var timePoint in _timeSeriesPoints)
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{
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points[++index] = timePoint.Point.Y;
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}
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return points;
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}
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@ -156,13 +139,13 @@ namespace OpenTabletDriverPlugins
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return avg / _reportRateAvg.Count;
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}
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private double[] CalcWeight()
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private double[] CalcWeight(double ratio)
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{
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var weights = new List<double>();
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var weightsNormalized = new List<double>();
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double weight = 1;
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foreach (var point in _timeSeriesPoints)
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weights.Add(weight *= 2);
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weights.Add(weight *= ratio);
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foreach (var _weight in weights)
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weightsNormalized.Add(_weight / weights[^1]);
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return weightsNormalized.ToArray();
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@ -170,18 +153,18 @@ namespace OpenTabletDriverPlugins
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#endregion Private Functions
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private int _samples = 6, _degree = 1, _ahead = 8;
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private double _compensation = 0, _weight = 2;
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private int _samples = 20, _degree = 2;
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private LinkedList<TimeSeriesPoint> _timeSeriesPoints = new LinkedList<TimeSeriesPoint>();
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private LinkedList<double> _reportRateAvg = new LinkedList<double>();
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private double _reportRate;
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private DateTime _lastTime = DateTime.Now;
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private double _compensation;
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private bool _normalize, _sync, _weighted;
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private bool _normalize;
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private int _screenWidth, _screenHeight;
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#region Controls
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[UnitProperty("Compensation", "ms")]
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[UnitProperty("Offset", "ms")]
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public double Compensation
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{
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set => CompensationFunc(ref _compensation, value);
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@ -195,14 +178,21 @@ namespace OpenTabletDriverPlugins
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get => _samples;
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}
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[Property("Degree")]
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[Property("Complexity")]
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public int Degree
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{
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set => DegreeFunc(ref _degree, value);
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get => _degree;
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}
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[BooleanProperty("Normalize", "Preprocess the input before performing regression. (may improve accuracy) Set Screen Dimensions below when enabling Normalization.")]
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[Property("Weight")]
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public double Weight
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{
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set => RaiseAndSetIfChanged(ref _weight, value);
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get => _weight;
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}
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[BooleanProperty("Normalize", "Preprocess the input. Set Screen Dimensions below when enabling Normalization.")]
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public bool Normalize
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{
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set => RaiseAndSetIfChanged(ref _normalize, value);
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@ -223,62 +213,38 @@ namespace OpenTabletDriverPlugins
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get => _screenHeight;
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}
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[BooleanProperty("Synchronize to Report Rate", "Compensation will be ignored in respect for tablet's report rate. Set below how many tablet reports to predict ahead.")]
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public bool Sync
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{
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set => RaiseAndSetIfChanged(ref _sync, value);
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get => _sync;
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}
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[Property("Reports Ahead")]
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public int Ahead
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{
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set => RaiseAndSetIfChanged(ref _ahead, value);
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get => _ahead;
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}
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[BooleanProperty("Exponential Weighted Polynomial Regression", "Well...")]
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public bool Weighted
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{
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set => RaiseAndSetIfChanged(ref _weighted, value);
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get => _weighted;
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}
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#endregion Controls
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#region Control Utility Functions
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private void CompensationFunc(ref double a, double value)
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{
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if (value > 30)
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Log.Write("ExpASFilter", "Unrealistic latency compensation. [Compensation: " + value + "ms]", true);
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if (value == 0)
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Log.Write("ExpASFilter", "Mode: Sub-Zero Latency Cursor Correction");
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else if (value > 0)
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{
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Log.Write("ExpASFilter", "Mode: Latency Compensation");
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if (value > 18)
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Log.Write("ExpASFilter", "Unrealistic latency compensation. [Compensation: " + value + "ms]", true);
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}
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else if (value < 0)
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Log.Write("ExpASFilter", "Mode: Interpolation");
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RaiseAndSetIfChanged(ref a, value);
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}
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private void SamplesFunc(ref int a, int value)
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{
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int minimum = Degree + 1;
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var suggested = Math.Pow(Degree, 2);
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if (value > 12)
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Log.Write("ExpASFilter",
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"Samples too high. Expect higher latency." +
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"[Samples: " + value + "]", true);
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else if (value <= minimum)
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if (value <= minimum)
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{
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Log.Write("ExpASFilter",
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"Samples too low for selected degree." +
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"[Samples: " + value + ", Required Minimum: " + minimum + "]", true);
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"[Samples: " + value + ", Requirement: >" + value + "]", true);
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RaiseAndSetIfChanged(ref a, minimum);
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return;
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}
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if (value <= suggested)
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Log.Write("ExpASFilter",
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"Samples might not be enough for an accurate prediction." +
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"[Samples: " + value + ", Suggestion: " + suggested + "]");
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RaiseAndSetIfChanged(ref a, value);
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}
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@ -286,11 +252,14 @@ namespace OpenTabletDriverPlugins
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{
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if (value == 0)
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{
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Log.Write("ExpASFilter", "Degree cannot be zero", true);
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Log.Write("ExpASFilter", "Complexity cannot be zero", true);
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}
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else if (value > 5)
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else if (value > 10)
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{
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Log.Write("ExpASFilter", "Degree too high, might cause instability and inaccuracy issues" +
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"[Suggestion: Degree <= 5]");
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"[Suggestion: (Degree <= 10, Normalization: enable)]");
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}
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RaiseAndSetIfChanged(ref a, value);
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}
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