public void ShouldAddObservations()
{
AddObservations(_histogram, 10L, 30L, 50L);
var histogram2 = new Histogram(Intervals);
AddObservations(histogram2, 10L, 20L, 25L);
_histogram.AddObservations(histogram2);
Assert.AreEqual(6L, _histogram.Count);
}
public void ShouldCorrectMeanForSkewInTopAndBottomPopulatedIntervals()
{
var intervals = new long[]{ 100, 110, 120, 130, 140, 150, 1000, 10000 };
var histogram = new Histogram(intervals);
for (long i = 100; i < 152; i++)
{
histogram.AddObservation(i);
}
Assert.AreEqual(125.02d, histogram.Mean);
}
public LatencyStepQueueEventProcessor(FunctionStep functionStep,
BlockingCollection<long> inputQueue,
BlockingCollection<long> outputQueue,
Histogram histogram, long nanoTimeCost, double ticksToNanos, long iterations)
{
_functionStep = functionStep;
_inputQueue = inputQueue;
_outputQueue = outputQueue;
_histogram = histogram;
_nanoTimeCost = nanoTimeCost;
_ticksToNanos = ticksToNanos;
_iterations = iterations;
}
public LatencyStepQueueConsumer(FunctionStep functionStep,
BlockingCollection<long> inputQueue,
BlockingCollection<long> outputQueue,
Histogram histogram,
long nanoTimeCost,
Stopwatch stopwatch)
{
this.functionStep = functionStep;
this.inputQueue = inputQueue;
this.outputQueue = outputQueue;
this.histogram = histogram;
this.nanoTimeCost = nanoTimeCost;
this.stopwatch = stopwatch;
}
/// <summary>
/// Add observations from another Histogram into this one.
/// Histograms must have the same intervals.
/// </summary>
/// <param name="histogram">histogram from which to add the observation counts.</param>
public void AddObservations(Histogram histogram)
{
if (_upperBounds.Length != histogram._upperBounds.Length)
{
throw new ArgumentException("Histograms must have matching intervals", "histogram");
}
for (int i = 0; i < _upperBounds.Length; i++)
{
if (_upperBounds[i] != histogram._upperBounds[i])
{
throw new ArgumentException("Histograms must have matching intervals", "histogram");
}
}
for (int i = 0; i < _counts.Length; i++)
{
_counts[i] += histogram._counts[i];
}
TrackRange(histogram._minValue);
TrackRange(histogram._maxValue);
}
private void InitHistogram()
{
if (_histogram == null)
{
var intervals = new long[31];
var intervalUpperBound = 1L;
for (var i = 0; i < intervals.Length - 1; i++)
{
intervalUpperBound *= 2;
intervals[i] = intervalUpperBound;
}
intervals[intervals.Length - 1] = long.MaxValue;
_histogram = new Histogram(intervals);
}
}
private void InitHistogram()
{
long[] intervals = new long[31];
long intervalUpperBound = 1L;
for (int i = 0, size = intervals.Length - 1; i < size; i++)
{
intervalUpperBound *= 2;
intervals[i] = intervalUpperBound;
}
intervals[intervals.Length - 1] = long.MaxValue;
_histogram = new Histogram(intervals);
}
public void ShouldGetFourNinesUpperBound()
{
var intervals = new long[]{ 1, 10, 100, 1000, 10000 };
var histogram = new Histogram(intervals);
for (long i = 1; i < 102; i++)
{
histogram.AddObservation(i);
}
Assert.AreEqual(1000L, histogram.FourNinesUpperBound);
}
public void SetUp()
{
_histogram = new Histogram(Intervals);
}
private static void AddObservations(Histogram histogram, params long[] observations)
{
foreach (var observation in observations)
{
histogram.AddObservation(observation);
}
}
public void ShouldThrowExceptionWhenIntervalsDoNotMatch()
{
var histogram2 = new Histogram(new[]{ 1L, 2L, 3L});
_histogram.AddObservations(histogram2);
}
public void ShouldNotAddObservation()
{
var histogram = new Histogram(new long[]{ 10, 20, 30 });
Assert.IsFalse(histogram.AddObservation(31L));
}
public void ShouldGetMeanObservation()
{
var intervals = new long[]{ 1, 10, 100, 1000, 10000 };
var histogram = new Histogram(intervals);
AddObservations(histogram, 1L, 7L, 10L, 10L, 11L, 144L);
Assert.AreEqual(32.67d, histogram.Mean);
}
