C# implementation of Thresholding algorithm used for peek (and through) detection from https://stackoverflow.com/questions/22583391/peak-signal-detection-in-realtime-timeseries-data/22771985

ThresholdingAlgo.cs

/// <summary>
/// Algo from: https://stackoverflow.com/questions/22583391/peak-signal-detection-in-realtime-timeseries-data/22771985
/// </summary>
public static (IList<double> avg, IList<double> sd, IList<int> detected)
    ThresholdingAlgo(this IList<double> values, int windowSize, double threshold, double influence){

    //number in constructor represent capacity, not size
    var avg = new List<double>(values.Count);
    var mad = new List<double>(values.Count);
    var filteredValues = new List<double>(values.Count); //used for calculating avg and sd
    var signals = new List<int>(values.Count);

    //init lists
    avg.AddRange(Enumerable.Repeat(double.NaN, values.Count));
    mad.AddRange(Enumerable.Repeat(double.NaN, values.Count));
    filteredValues.AddRange(values.Take(windowSize));
    signals.AddRange(Enumerable.Repeat(0, values.Count));

    //eval first step of running mean/mad (insert at index windowSize-1)
    avg[windowSize - 1] = filteredValues.Take(windowSize).Average();
    mad[windowSize - 1] = filteredValues.Take(windowSize).MedianAbsoluteDeviation(); //used mad instead of sd from original algo

    for (int i = windowSize; i < values.Count; i++)
    {
        //adding one to mad to combat false detections when mad was really low, not part of original algo
        if (Math.Abs(values[i]) > avg[i - 1] + threshold * (1 + mad[i - 1]))
        {
            if (values[i] > avg[i - 1])
                signals[i] = 1;
            else
                signals[i] = -1;

            filteredValues.Add(influence * values[i] + (1 - influence) * filteredValues[i - 1]);
        }
        else
        {
            filteredValues.Add(values[i]);
        }

        //bug - takes windowsSize + 1 value to count
        //left intentionally in code to achieve same results as referential implementation/pseudocode
        //should start at (i - windowSize + 1) and take only (windowSize items)
        avg[i] = filteredValues.Skip(i - windowSize).Take(windowSize + 1).Average();
        mad[i] = filteredValues.Skip(i - windowSize).Take(windowSize + 1).MedianAbsoluteDeviation();
    }

    return (avg, mad, signals);
}