public static void Print([NotNull] this ITestOutputHelper output, [NotNull] string title, [NotNull] Histogram histogram)
{
var values = histogram.GetAllValues().CopyToArray();
double mValue = MValueCalculator.Calculate(values);
var cultureInfo = TestCultureInfo.Instance;
var binSizeInterval = TimeInterval.FromNanoseconds(histogram.BinSize);
output.WriteLine($"=== {title}:Short (BinSize={binSizeInterval.ToString(cultureInfo)}, mValue={mValue.ToString("0.##", cultureInfo)}) ===");
output.WriteLine(histogram.ToString(histogram.CreateNanosecondFormatter(cultureInfo, "0.0000")));
output.WriteLine($"=== {title}:Full (BinSize={binSizeInterval.ToString(cultureInfo)}, mValue={mValue.ToString("0.##", cultureInfo)}) ===");
output.WriteLine(histogram.ToString(histogram.CreateNanosecondFormatter(cultureInfo, "0.0000"), full: true));
}
public void Run()
{
var random = new Random(42);
var data = new List <double>();
data.AddRange(new NormalDistribution(mean: 20, stdDev: 1).Random(random).Next(200));
data.AddRange(new NormalDistribution(mean: 22, stdDev: 1).Random(random).Next(200));
List <double>
unimodal = new List <double>(),
bimodal = new List <double>(),
trimodal = new List <double>();
unimodal.AddRange(new NormalDistribution(mean: 20, stdDev: 1).Random(random).Next(200));
bimodal.AddRange(new NormalDistribution(mean: 20, stdDev: 1).Random(random).Next(200));
bimodal.AddRange(new NormalDistribution(mean: 30, stdDev: 1).Random(random).Next(200));
trimodal.AddRange(new NormalDistribution(mean: 20, stdDev: 1).Random(random).Next(200));
trimodal.AddRange(new NormalDistribution(mean: 30, stdDev: 1).Random(random).Next(200));
trimodal.AddRange(new NormalDistribution(mean: 40, stdDev: 1).Random(random).Next(200));
Console.WriteLine("Unimodal : " + MValueCalculator.Calculate(unimodal));
Console.WriteLine("Bimodal : " + MValueCalculator.Calculate(bimodal));
Console.WriteLine("Trimodal : " + MValueCalculator.Calculate(trimodal));
}
public void Run()
{
var random = new RandomDistribution(42);
var data = new List <double>();
data.AddRange(random.Gaussian(200, mean: 20));
data.AddRange(random.Gaussian(200, mean: 22));
List <double>
unimodal = new List <double>(),
bimodal = new List <double>(),
trimodal = new List <double>();
unimodal.AddRange(random.Gaussian(200, mean: 20));
bimodal.AddRange(random.Gaussian(200, mean: 20));
bimodal.AddRange(random.Gaussian(200, mean: 30));
trimodal.AddRange(random.Gaussian(200, mean: 20));
trimodal.AddRange(random.Gaussian(200, mean: 30));
trimodal.AddRange(random.Gaussian(200, mean: 40));
Console.WriteLine("Unimodal : " + MValueCalculator.Calculate(unimodal));
Console.WriteLine("Bimodal : " + MValueCalculator.Calculate(bimodal));
Console.WriteLine("Trimodal : " + MValueCalculator.Calculate(trimodal));
}
// code and magic values taken from BenchmarkDotNet.Analysers.MultimodalDistributionAnalyzer
// See http://www.brendangregg.com/FrequencyTrails/modes.html
internal static string GetModalInfo(Benchmark benchmark)
{
if (benchmark.Statistics.N < 12) // not enough data to tell
{
return(null);
}
double mValue = MValueCalculator.Calculate(benchmark.Statistics.OriginalValues);
if (mValue > 4.2)
{
return("multimodal");
}
else if (mValue > 3.2)
{
return("bimodal");
}
else if (mValue > 2.8)
{
return("several?");
}
return(null);
}
protected override IEnumerable <Conclusion> AnalyseReport(BenchmarkReport report, Summary summary)
{
var statistics = report.ResultStatistics;
if (statistics == null || statistics.N < EngineResolver.DefaultMinWorkloadIterationCount)
{
yield break;
}
double mValue = MValueCalculator.Calculate(statistics.OriginalValues);
if (mValue > 4.2)
{
yield return(Create("is multimodal", mValue, report, summary.Style.CultureInfo));
}
else if (mValue > 3.2)
{
yield return(Create("is bimodal", mValue, report, summary.Style.CultureInfo));
}
else if (mValue > 2.8)
{
yield return(Create("can have several modes", mValue, report, summary.Style.CultureInfo));
}
}
// code and magic values taken from BenchmarkDotNet.Analysers.MultimodalDistributionAnalyzer
// See http://www.brendangregg.com/FrequencyTrails/modes.html
private static Modality GetModalInfo(Benchmark benchmark)
{
if (benchmark.Statistics.N < 12) // not enough data to tell
{
return(Modality.Single);
}
double mValue = MValueCalculator.Calculate(benchmark.GetOriginalValues());
if (mValue > 4.2)
{
return(Modality.Multimodal);
}
else if (mValue > 3.2)
{
return(Modality.Bimodal);
}
else if (mValue > 2.8)
{
return(Modality.Several);
}
return(Modality.Single);
}
public static void Run(MValueCalculatorOptions options)
{
var data = options.GetSourceArray();
Console.WriteLine(MValueCalculator.Calculate(data));
}
public static string ToString(this Statistics s, CultureInfo cultureInfo, Func <double, string> formatter, bool calcHistogram = false)
{
if (s == null)
{
return(NullSummaryMessage);
}
string listSeparator = cultureInfo.GetActualListSeparator();
var builder = new StringBuilder();
string errorPercent = (s.StandardError / s.Mean * 100).ToString("0.00", cultureInfo);
var ci = s.ConfidenceInterval;
string ciMarginPercent = (ci.Margin / s.Mean * 100).ToString("0.00", cultureInfo);
double mValue = MValueCalculator.Calculate(s.OriginalValues);
builder.Append("Mean = ");
builder.Append(formatter(s.Mean));
builder.Append(listSeparator);
builder.Append(" StdErr = ");
builder.Append(formatter(s.StandardError));
builder.Append(" (");
builder.Append(errorPercent);
builder.Append("%)");
builder.Append(listSeparator);
builder.Append(" N = ");
builder.Append(s.N.ToString(cultureInfo));
builder.Append(listSeparator);
builder.Append(" StdDev = ");
builder.Append(formatter(s.StandardDeviation));
builder.AppendLine();
builder.Append("Min = ");
builder.Append(formatter(s.Min));
builder.Append(listSeparator);
builder.Append(" Q1 = ");
builder.Append(formatter(s.Q1));
builder.Append(listSeparator);
builder.Append(" Median = ");
builder.Append(formatter(s.Median));
builder.Append(listSeparator);
builder.Append(" Q3 = ");
builder.Append(formatter(s.Q3));
builder.Append(listSeparator);
builder.Append(" Max = ");
builder.Append(formatter(s.Max));
builder.AppendLine();
builder.Append("IQR = ");
builder.Append(formatter(s.InterquartileRange));
builder.Append(listSeparator);
builder.Append(" LowerFence = ");
builder.Append(formatter(s.LowerFence));
builder.Append(listSeparator);
builder.Append(" UpperFence = ");
builder.Append(formatter(s.UpperFence));
builder.AppendLine();
builder.Append("ConfidenceInterval = ");
builder.Append(s.ConfidenceInterval.ToString(formatter));
builder.Append(listSeparator);
builder.Append(" Margin = ");
builder.Append(formatter(ci.Margin));
builder.Append(" (");
builder.Append(ciMarginPercent);
builder.Append("% of Mean)");
builder.AppendLine();
builder.Append("Skewness = ");
builder.Append(s.Skewness.ToString("0.##", cultureInfo));
builder.Append(listSeparator);
builder.Append(" Kurtosis = ");
builder.Append(s.Kurtosis.ToString("0.##", cultureInfo));
builder.Append(listSeparator);
builder.Append(" MValue = ");
builder.Append(mValue.ToString("0.##", cultureInfo));
builder.AppendLine();
if (calcHistogram)
{
var histogram = HistogramBuilder.Adaptive.Build(s.OriginalValues);
builder.AppendLine("-------------------- Histogram --------------------");
builder.AppendLine(histogram.ToString(formatter));
builder.AppendLine("---------------------------------------------------");
}
return(builder.ToString().Trim());
}
