public void Test_PeakDetectionAlgorithm()
{
// Arrange
var input = new List <double> {
1.0, 1.0, 1.1, 1.0, 0.9, 1.0, 1.0, 1.1, 1.0, 0.9, 1.0,
1.1, 1.0, 1.0, 0.9, 1.0, 1.0, 1.1, 1.0, 1.0, 1.0, 1.0, 1.1, 0.9, 1.0, 1.1, 1.0, 1.0, 0.9,
1.0, 1.1, 1.0, 1.0, 1.1, 1.0, 0.8, 0.9, 1.0, 1.2, 0.9, 1.0, 1.0, 1.1, 1.2, 1.0, 1.5, 1.0,
3.0, 2.0, 5.0, 3.0, 2.0, 1.0, 1.0, 1.0, 0.9, 1.0, 1.0, 3.0, 2.6, 4.0, 3.0, 3.2, 2.0, 1.0,
1.0, 0.8, 4.0, 4.0, 2.0, 2.5, 1.0, 1.0, 1.0
};
var timeStamps = new List <double>(new double[input.Count]);
var expectedPeaks = new List <double> {
45, 49, 60, 68
};
List <Complex> inputSignal = ToComplex(input.ToArray()).ToList();
for (int i = 0; i < timeStamps.Count; i++)
{
timeStamps[i] = i;
}
int lag = 30;
double threshold = 5;
double influence = 0;
// Act
PeakDetectionOutput detector = PeakDetection.PeakDetectionAlgorithm(inputSignal, timeStamps, lag, threshold, influence);
// Assert
Assert.Equal(expectedPeaks.Count, detector.peakIndexes.Count);
for (int i = 0; i < expectedPeaks.Count; i++)
{
Assert.Equal(expectedPeaks.ElementAt(i), detector.peakIndexes.ElementAt(i));
}
}
/// <summary>
/// Main entry point
/// </summary>
/// <param name="args">= Input program arguments</param>
static void Main(string[] args)
{
try
{
Dictionary <string, string> progArgs = Parse(args);
// Program arguments
double fs = Convert.ToDouble(progArgs["sampling"]);
double Ts = 1.0 / fs;
double fc = Convert.ToDouble(progArgs["carrier"]);
double passBand = Convert.ToDouble(progArgs["passband"]);
double stopBand = Convert.ToDouble(progArgs["cutoffband"]);
double gainDeviation = Convert.ToDouble(progArgs["gaindev"]);
int peakLag = Convert.ToInt32(progArgs["peaklag"]);
double peakThreshold = Convert.ToDouble(progArgs["peakthreshold"]);
double peakInfluence = Convert.ToDouble(progArgs["peakinfluence"]);
double tiThreshold = Convert.ToDouble(progArgs["tithreshold"]);
Dsp Signal = new Dsp();
// Low pass FIR filter
List <Complex> firImpulseResponse = Signal.KaiserWindowFir(gainDeviation, passBand, stopBand, fs);
// FIR filter length
int M = firImpulseResponse.Count;
// Block length
int N = Signal.MinBlockLength(M);
// FFT input sequence length
int L = N - M + 1;
Complex[] appendSequence = new Complex[L - 1];
Array.Clear(appendSequence, 0, L - 1);
// FIR filter frequency response
Complex[] firFFT = Signal.ComputePaddedFFT(ref firImpulseResponse, N, appendSequence.ToList());
// Main class output values
List <double> timeStamps = new List <double>();
List <double> peakTimeStamps = new List <double>();
List <double> peakTimeIntervals = new List <double>();
List <double> timeIntervalsMovingAverage = new List <double>();
List <int> peakIndexes = new List <int>();
List <int> outliersTimeIntervals = null;
// Read data from input file
using StreamReader inputFile = new StreamReader(progArgs["inputfile"]);
WriteToFile outFile = new WriteToFile(progArgs["outputfile"]);
WriteToFile timeIntervalFile = new WriteToFile(progArgs["tifile"]);
inputFile.BaseStream.Seek(0, SeekOrigin.Begin);
string str = inputFile.ReadLine();
double dLSBValue = -1;
double dVoltageValue = -1;
double dValue = 0.0;
double dAverage = 0.0;
double dTimeStamp = 0.0;
double dPhase = 0.0;
double timeIntervalsMoveAverage = 0.0;
double timeIntervalsMoveVariance = 0.0;
double lastPeakTimeStamp = 0.0;
int iNumSamples = 1;
int numDetections = 0;
int numMovingAverageSamples = 0;
while (str != null)
{
string[] sDataValues = str.Split(',');
try
{
dTimeStamp = ((double)iNumSamples - 1.0) * Ts;
dLSBValue = Convert.ToDouble(sDataValues[0]);
dVoltageValue = Convert.ToDouble(sDataValues[1]);
dAverage = ((double)iNumSamples - 1.0) / ((double)iNumSamples) * dAverage + dVoltageValue / ((double)iNumSamples);
// Remove DC offset
dValue = dVoltageValue - dAverage;
// Extract I and Q from signal and get base band signal
bool bPeakDetection = Signal.AcquireSignal(dValue, dPhase, dTimeStamp, fc, L, ref firFFT);
// Perform peak detection every L samples of the input sequence found from FFT transform
if (bPeakDetection)
{
PeakDetectionOutput detector = PeakDetection.PeakDetectionAlgorithm(
Signal.baseBandSignal.GetRange(numDetections * L, L),
Signal.timeStamp.GetRange(numDetections * L, L),
peakLag,
peakThreshold,
peakInfluence,
lastPeakTimeStamp,
numDetections * L
);
// Shift by L samples
numDetections += 1;
// Compute moving average of time intervals
numMovingAverageSamples += detector.peakTimeIntervals.Count;
outliersTimeIntervals = PeakDetection.TimeIntervalOutlierDetection(
detector.peakTimeIntervals,
numMovingAverageSamples,
timeIntervalsMoveAverage,
ref timeIntervalsMoveVariance,
tiThreshold
);
double currentWindowSum = detector.peakTimeIntervals.Sum();
timeIntervalsMoveAverage =
(numMovingAverageSamples - detector.peakTimeIntervals.Count) *
timeIntervalsMoveAverage / numMovingAverageSamples +
currentWindowSum / numMovingAverageSamples;
// Time stamp for the next block of data to find the time intervals
if (detector.peakTimeStamps.Count > 0)
{
lastPeakTimeStamp = detector.peakTimeStamps.Last();
}
// Store outputs either list or write to a file
timeIntervalFile.SummaryOutliers(
detector,
outliersTimeIntervals,
timeIntervalsMoveAverage,
Math.Sqrt(timeIntervalsMoveVariance),
tiThreshold
);
timeIntervalsMovingAverage.Add(timeIntervalsMoveAverage);
peakTimeStamps.AddRange(detector.peakTimeStamps);
peakIndexes.AddRange(detector.peakIndexes);
peakTimeIntervals.AddRange(detector.peakTimeIntervals);
}
timeStamps.Add(dTimeStamp);
iNumSamples += 1;
}
catch (FormatException)
{
}
catch (IndexOutOfRangeException)
{
}
str = inputFile.ReadLine();
}
Signal.LastSamplesConvolution(ref firFFT, L);
SignalOutput(outFile, Signal.baseBandSignal);
outFile.outFileHandler.Close();
timeIntervalFile.outFileHandler.Close();
Console.WriteLine("End of Test");
}
catch (Exception e)
{
Console.WriteLine(e);
}
}