public void GetProbabilityValuesForHistogramTest()
{
// We will pass in a sorted sequence of 10 pairs of values, each pair has an iterator
// numbered 0-9, and a corresponding value between 0-4, which repeats after each increment
// of five by the iterator, so each pair has one duplicate value in the sequence
// (e.g., (0,0),(1,1),(2,2),...(5,0),(6,1),(7,2),...(9,4) ).
// The GetProbabilityValues method calculates the number of packet counts (the pair values),
// then calculates the probability for each pair value, and returns a sorted sequence of
// pairs with the probability for each pair value.
// So we should get back a sequence of five pairs with the probabilities for the original
// pair values. For example, since the pair values total 20, the probability for a value
// of 2 is 2/20 = 0.1. So the returned sequence should be (0,0),(1,0.1),(2,0.2),(3,0.3),(4,0.4).
// Arrange
Dictionary<int, int> histogram = new Dictionary<int, int>();
for (int i = 0; i < 10; i++)
{
histogram.Add(i,i % 5);
}
CalculateProbability cp = new CalculateProbability(histogram);
// Act
Dictionary<int, decimal> sortedProbabilities = new Dictionary<int, decimal>();
sortedProbabilities = cp.GetProbabilityValues();
bool results = true;
if(sortedProbabilities.Count != 5)
{
results = false;
}
decimal expectedProbability = 0M;
foreach (var pair in sortedProbabilities)
{
if(pair.Value != expectedProbability)
{
results = false;
}
expectedProbability = expectedProbability + 0.1M;
}
// Assert
Assert.IsTrue(results);
}
private void CalculateSingleHistogramProbability(BindingList<BatchIntervalMarked> batchIntervalsCollection, BatchType batchType, CurrentCaptureFile captureFile)
{
BindingList<BatchIntervalMarked> batchIntervals = new BindingList<BatchIntervalMarked>();
batchIntervals = batchIntervalsCollection;
SortedDictionary<int, decimal> histogramProbabilities = new SortedDictionary<int, decimal>();
int histogramBinSize = AnalysisConfiguration.HistogramBinSize;
histogramProbabilities = new CalculateProbability(batchIntervals).GetProbabilityByPacketRange(_TrimZeroPacketIntervals, histogramBinSize);
// Convert histogram probabilities to Histogram type collection
BindingList<SingleHistogram> singleHistogramProbabilityData = new BindingList<SingleHistogram>();
foreach (KeyValuePair<int, decimal> data in histogramProbabilities)
{
SingleHistogram h = new SingleHistogram();
h.CaptureBatchId = captureFile.CaptureBatchId;
h.Interval = data.Key;
h.Probability = data.Value;
h.BatchType = Convert.ToInt32(batchType);
h.CaptureState = Convert.ToInt32(captureFile.CaptureState);
singleHistogramProbabilityData.Add(h);
}
// Save histogram data
SingleHistogramData shd = new SingleHistogramData(singleHistogramProbabilityData);
shd.InsertSingleHistogramData();
}
private void CalculateCumulativeHistogramProbability(BindingList<BatchIntervalMarked> batchIntervalsCollection, BatchType batchType, CaptureState captureState)
{
BindingList<BatchIntervalMarked> batchIntervals = new BindingList<BatchIntervalMarked>();
batchIntervals = batchIntervalsCollection;
SortedDictionary<int, decimal> histogramProbabilities = new SortedDictionary<int, decimal>();
int histogramBinSize = AnalysisConfiguration.HistogramBinSize;
histogramProbabilities = new CalculateProbability(batchIntervals).GetProbabilityByPacketRange(_TrimZeroPacketIntervals, histogramBinSize);
// Update the cumulative intervals for calculating cumulative probability distributions
switch(captureState)
{
case CaptureState.Marked:
_CumulativeMarkedProbabilities = histogramProbabilities;
break;
case CaptureState.Unmarked:
_CumulativeUnmarkedProbabilities = histogramProbabilities;
break;
}
// Convert histogram probabilities to Histogram type collection
BindingList<CumulativeHistogram> cumulativeHistogramProbabilityData = new BindingList<CumulativeHistogram>();
foreach (KeyValuePair<int, decimal> data in histogramProbabilities)
{
CumulativeHistogram h = new CumulativeHistogram();
h.Interval = data.Key;
h.Probability = data.Value;
h.BatchType = Convert.ToInt32(batchType);
h.CaptureState = Convert.ToInt32(captureState);
cumulativeHistogramProbabilityData.Add(h);
}
// Save histogram data
CumulativeHistogramData chd = new CumulativeHistogramData(cumulativeHistogramProbabilityData);
chd.InsertCumulativeHistogramData();
}
public bool CalculateSingleBatchStatisticsForLastTwoBatches()
{
bool result = false;
// Calculate single batch statistics
// Get the last marked and unmarked batches and add them to the graph
BindingList<CurrentCaptureFile> lastBatchIds = new BindingList<CurrentCaptureFile>();
ProcessCapturePackets pcp = new ProcessCapturePackets();
lastBatchIds = pcp.GetLastCaptureBatchIds();
foreach (CurrentCaptureFile file in lastBatchIds)
{
BindingList<BatchIntervalMarked> batchIntervals = new BindingList<BatchIntervalMarked>();
// Calculate probabilities
batchIntervals = pcp.GetMarkedBatchIntervals(file.CaptureBatchId);
int histogramBinSize = Convert.ToInt32(_HistogramBinSize);
SortedDictionary<int, decimal> probabilities = new CalculateProbability(batchIntervals).GetProbabilityByPacketRange(_TrimZeroPacketIntervals, histogramBinSize);
}
return result;
}
public bool CalculateSingleBatchStatistics()
{
bool result = false;
// Calculate single batch statistics
//// Get the last marked and unmarked batches and add them to the graph
//int lastBatchId = 0;
ProcessCapturePackets pcp = new ProcessCapturePackets();
//lastBatchId = pcp.GetLastCaptureBatchId();
CurrentCaptureFile captureFile = new CurrentCaptureFile();
CaptureFileData cfd = new CaptureFileData();
//captureFile = cfd.GetLastCaptureBatchRecord();
captureFile = cfd.GetCurrentCaptureFile(_CaptureFileName);
// Set the global variable
_CaptureState = captureFile.CaptureState;
BindingList<BatchIntervalMarked> batchIntervals = new BindingList<BatchIntervalMarked>();
// Calculate probabilities
batchIntervals = pcp.GetMarkedBatchIntervals(captureFile.CaptureBatchId);
int histogramBinSize = Convert.ToInt32(_HistogramBinSize);
SortedDictionary<int, decimal> probabilities = new CalculateProbability(batchIntervals).GetProbabilityByPacketRange(_TrimZeroPacketIntervals, histogramBinSize);
BatchStatistics markedSingleStats = new BatchStatistics();
BatchStatistics unmarkedSingleStats = new BatchStatistics();
// Add the results to the DisplayStatistics table
DisplayStatisticsData dsd = new DisplayStatisticsData();
if(captureFile.CaptureState == CaptureState.Marked)
{
markedSingleStats = CalculateBatchStatistics(batchIntervals, CaptureState.Marked, BatchType.Single);
}
else
{
unmarkedSingleStats = CalculateBatchStatistics(batchIntervals, CaptureState.Unmarked, BatchType.Single);
}
return result;
}
public void CalculateCumulativeProbabilityDistribution(CaptureState captureState)
{
// Note: cumulative histogram intervals must have previously been calculated in order to calculate cumulative probabilities
//SortedDictionary<int, decimal> _CumulativeMarkedProbabilities = new SortedDictionary<int, decimal>();
//SortedDictionary<int, decimal> _CumulativeUnmarkedProbabilities = new SortedDictionary<int, decimal>();
//_CumulativeMarkedProbabilities = new CalculateProbability(batchIntervals).GetProbabilityByPacketRange(_TrimZeroPacketIntervals, histogramBinSize);
// Get the batch intervals
BindingList<BatchIntervalMarked> unmarkedBatchIntervals = new BindingList<BatchIntervalMarked>();
BindingList<BatchIntervalMarked> markedBatchIntervals = new BindingList<BatchIntervalMarked>();
BindingList<CumulativeProbabilityDistribution> distribution = new BindingList<CumulativeProbabilityDistribution>();
//CumulativeProbabilityDistributionData cumProbDistData = new CumulativeProbabilityDistributionData();
using (var uow = new UnitOfWorkCumulativeProbability())
{
//using (var cpdRepository = new CumulativeProbabilityDistributionRepository(new UnitOfWorkCumulativeProbability()))
using (var cpdRepository = new CumulativeProbabilityDistributionRepository(uow))
{
//// Delete any existing cumulative probability distribution data for the captureState
//cumProbDistData.DeleteCumulativeProbabilityDistribution(captureState);
cpdRepository.DeleteBatch(captureState);
// Add the newly calculated cumulative probability distribution
switch (captureState)
{
case CaptureState.Marked:
if (_CumulativeMarkedProbabilities != null)
{
SortedDictionary<int, decimal> markedProbabilities = new CalculateProbability(markedBatchIntervals).GetCumulativeProbabilityDistribution(_CumulativeMarkedProbabilities);
// Convert to CumulativeProbabilityDistribution type
foreach (KeyValuePair<int, decimal> item in markedProbabilities)
{
CumulativeProbabilityDistribution cpd = new CumulativeProbabilityDistribution();
cpd.CaptureState = (int)CaptureState.Marked;
cpd.Interval = item.Key;
cpd.Probability = Math.Round(item.Value, 10);
//distribution.Add(cpd);
cpdRepository.InsertOrUpdate(cpd);
uow.Save();
}
}
//// Save to database
//cumProbDistData.InsertCumulativeProbabilityDistribution(distribution);
break;
case CaptureState.Unmarked:
if (_CumulativeUnmarkedProbabilities != null)
{
SortedDictionary<int, decimal> unmarkedProbabilities = new CalculateProbability(unmarkedBatchIntervals).GetCumulativeProbabilityDistribution(_CumulativeUnmarkedProbabilities);
// Convert to CumulativeProbabilityDistribution type
foreach (KeyValuePair<int, decimal> item in unmarkedProbabilities)
{
CumulativeProbabilityDistribution cpd = new CumulativeProbabilityDistribution();
cpd.CaptureState = (int)CaptureState.Unmarked;
cpd.Interval = item.Key;
//cpd.Probability = Convert.ToDecimal(String.Format("{0,10}", item.Value.ToString("D")));
cpd.Probability = Math.Round(item.Value, 10);
//distribution.Add(cpd);
cpdRepository.InsertOrUpdate(cpd);
uow.Save();
}
}
//// Save to database
//cumProbDistData.InsertCumulativeProbabilityDistribution(distribution);
break;
}
}
}
}
