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Added exponential distributions

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This commit is contained in:
Thorsten Sommer 2020-10-31 14:00:25 +01:00
parent b437aac4c8
commit 2f4c8b3cc9
5 changed files with 202 additions and 64 deletions
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36
FastRng/Double/Distributions/Exponential.cs
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@ -1,36 +0,0 @@
using System;
using System.Threading;
using System.Threading.Tasks;
namespace FastRng.Double.Distributions
{
public sealed class Exponential : IDistribution
{
private double mean = 1.0;
public IRandom Random { get; set; }
public double Mean
{
get => this.mean;
set
{
if(value <= 0.0)
throw new ArgumentOutOfRangeException(message: "Mean must be greater than 0", null);
this.mean = value;
}
}
public async ValueTask<double> GetDistributedValue(CancellationToken token = default)
{
if (this.Random == null)
return double.NaN;
if(this.Mean == 1.0)
return -Math.Log(await this.Random.GetUniform(token));
else
return this.Mean * -Math.Log(await this.Random.GetUniform(token));
}
}
}

35
FastRng/Double/Distributions/ExponentialLa10.cs Normal file
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@ -0,0 +1,35 @@
using System;
using System.Threading;
using System.Threading.Tasks;
namespace FastRng.Double.Distributions
{
public sealed class ExponentialLa10 : IDistribution
{
private const double LAMBDA = 10.0;
private const double CONSTANT = 0.1106;
private ShapeFitter fitter;
private IRandom random;
public IRandom Random
{
get => this.random;
set
{
this.random = value;
this.fitter = new ShapeFitter(ExponentialLa10.ShapeFunction, this.random, 100);
}
}
private static double ShapeFunction(double x) => CONSTANT * LAMBDA * Math.Exp(-LAMBDA * x);
public async ValueTask<double> GetDistributedValue(CancellationToken token = default)
{
if (this.Random == null)
return double.NaN;
return await this.fitter.NextNumber(token);
}
}
}

35
FastRng/Double/Distributions/ExponentialLa5.cs Normal file
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@ -0,0 +1,35 @@
using System;
using System.Threading;
using System.Threading.Tasks;
namespace FastRng.Double.Distributions
{
public sealed class ExponentialLa5 : IDistribution
{
private const double LAMBDA = 5.0;
private const double CONSTANT = 0.2103;
private ShapeFitter fitter;
private IRandom random;
public IRandom Random
{
get => this.random;
set
{
this.random = value;
this.fitter = new ShapeFitter(ExponentialLa5.ShapeFunction, this.random, 100);
}
}
private static double ShapeFunction(double x) => CONSTANT * LAMBDA * Math.Exp(-LAMBDA * x);
public async ValueTask<double> GetDistributedValue(CancellationToken token = default)
{
if (this.Random == null)
return double.NaN;
return await this.fitter.NextNumber(token);
}
}
}

104
FastRngTests/Double/Distributions/ExponentialLa10.cs Normal file
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@ -0,0 +1,104 @@
using System;
using System.Diagnostics.CodeAnalysis;
using System.Linq;
using System.Threading.Tasks;
using FastRng.Double;
using NUnit.Framework;
namespace FastRngTests.Double.Distributions
{
[ExcludeFromCodeCoverage]
public class ExponentialLa10
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialDistribution01()
{
var dist = new FastRng.Double.Distributions.ExponentialLa10();
var fqa = new FrequencyAnalysis();
var rng = new MultiThreadedRng();
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await rng.NextNumber(dist));
rng.StopProducer();
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(1.00075018434777).Within(0.05));
Assert.That(result[1], Is.EqualTo(0.905516212904248).Within(0.05));
Assert.That(result[2], Is.EqualTo(0.81934495207398).Within(0.05));
Assert.That(result[21], Is.EqualTo(0.122548293148741).Within(0.01));
Assert.That(result[22], Is.EqualTo(0.110886281157421).Within(0.01));
Assert.That(result[23], Is.EqualTo(0.10033405633809).Within(0.01));
Assert.That(result[50], Is.EqualTo(0.00674300170146).Within(0.005));
Assert.That(result[75], Is.EqualTo(0.000553499285385).Within(0.001));
Assert.That(result[85], Is.EqualTo(0.000203621007796).Within(0.001));
Assert.That(result[90], Is.EqualTo(0.00012350238419).Within(0.001));
Assert.That(result[97], Is.EqualTo(0.0000613294689720).Within(0.0008));
Assert.That(result[98], Is.EqualTo(0.0000554931983541).Within(0.0008));
Assert.That(result[99], Is.EqualTo(0.0000502123223173).Within(0.0008));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange01()
{
var dist = new FastRng.Double.Distributions.ExponentialLa10();
var rng = new MultiThreadedRng();
var samples = new double[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await rng.NextNumber(-1.0, 1.0, dist);
rng.StopProducer();
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange02()
{
var dist = new FastRng.Double.Distributions.ExponentialLa10();
var rng = new MultiThreadedRng();
var samples = new double[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await rng.NextNumber(0.0, 1.0, dist);
rng.StopProducer();
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0), "Max is out of range");
}
[Test] [Category(TestCategories.COVER)] [Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange03()
{
var rng = new MultiThreadedRng();
var dist = new FastRng.Double.Distributions.ExponentialLa10 { Random = rng }; // Test default parameters
var samples = new double[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.GetDistributedValue();
rng.StopProducer();
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task NoRandomNumberGenerator01()
{
var dist = new FastRng.Double.Distributions.ExponentialLa10();
Assert.DoesNotThrowAsync(async () => await dist.GetDistributedValue());
Assert.That(await dist.GetDistributedValue(), Is.NaN);
}
}
}

56
FastRngTests/Double/Distributions/Exponential.cs → FastRngTests/Double/Distributions/ExponentialLa5.cs
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@ -8,29 +8,40 @@ using NUnit.Framework;
namespace FastRngTests.Double.Distributions
{
[ExcludeFromCodeCoverage]
public class Exponential
public class ExponentialLa5
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialDistribution01()
{
const double MEAN = 1.5;
const double VARIANCE = MEAN * MEAN;
var dist = new FastRng.Double.Distributions.Exponential{ Mean = MEAN };
var stats = new RunningStatistics();
var dist = new FastRng.Double.Distributions.ExponentialLa5();
var fqa = new FrequencyAnalysis();
var rng = new MultiThreadedRng();
for (var n = 0; n < 100_000; n++)
stats.Push(await rng.NextNumber(dist));
fqa.CountThis(await rng.NextNumber(dist));
rng.StopProducer();
TestContext.WriteLine($"mean={MEAN} vs. {stats.Mean}");
TestContext.WriteLine($"variance={VARIANCE} vs {stats.Variance}");
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(stats.Mean, Is.EqualTo(MEAN).Within(0.1), "Mean is out of range");
Assert.That(stats.Variance, Is.EqualTo(VARIANCE).Within(0.1), "Variance is out of range");
Assert.That(result[0], Is.EqualTo(1.0002177398625).Within(0.05));
Assert.That(result[1], Is.EqualTo(0.951436545064811).Within(0.05));
Assert.That(result[2], Is.EqualTo(0.905034437210948).Within(0.05));
Assert.That(result[21], Is.EqualTo(0.35001394450853).Within(0.05));
Assert.That(result[22], Is.EqualTo(0.332943563002074).Within(0.05));
Assert.That(result[23], Is.EqualTo(0.31670571382568).Within(0.05));
Assert.That(result[50], Is.EqualTo(0.082102871800213).Within(0.01));
Assert.That(result[75], Is.EqualTo(0.023522866606758).Within(0.01));
Assert.That(result[85], Is.EqualTo(0.014267339801329).Within(0.01));
Assert.That(result[90], Is.EqualTo(0.011111415409621).Within(0.01));
Assert.That(result[97], Is.EqualTo(0.007830082099077).Within(0.008));
Assert.That(result[98], Is.EqualTo(0.007448204488898).Within(0.008));
Assert.That(result[99], Is.EqualTo(0.007084951269538).Within(0.008));
}
[Test]
@ -38,10 +49,11 @@ namespace FastRngTests.Double.Distributions
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange01()
{
var dist = new FastRng.Double.Distributions.ExponentialLa5();
var rng = new MultiThreadedRng();
var samples = new double[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await rng.NextNumber(-1.0, 1.0, new FastRng.Double.Distributions.Exponential());
samples[n] = await rng.NextNumber(-1.0, 1.0, dist);
rng.StopProducer();
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0), "Min out of range");
@ -53,10 +65,11 @@ namespace FastRngTests.Double.Distributions
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange02()
{
var dist = new FastRng.Double.Distributions.ExponentialLa5();
var rng = new MultiThreadedRng();
var samples = new double[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await rng.NextNumber(0.0, 1.0, new FastRng.Double.Distributions.Exponential());
samples[n] = await rng.NextNumber(0.0, 1.0, dist);
rng.StopProducer();
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0), "Min is out of range");
@ -67,7 +80,7 @@ namespace FastRngTests.Double.Distributions
public async Task TestExponentialGeneratorWithRange03()
{
var rng = new MultiThreadedRng();
var dist = new FastRng.Double.Distributions.Exponential { Random = rng }; // Test default parameters
var dist = new FastRng.Double.Distributions.ExponentialLa5 { Random = rng }; // Test default parameters
var samples = new double[1_000];
for (var n = 0; n < samples.Length; n++)
@ -78,25 +91,12 @@ namespace FastRngTests.Double.Distributions
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void ParameterTest01()
{
var dist = new FastRng.Double.Distributions.Exponential();
Assert.Throws<ArgumentOutOfRangeException>(() => dist.Mean = 0);
Assert.Throws<ArgumentOutOfRangeException>(() => dist.Mean = -78);
Assert.DoesNotThrow(() => dist.Mean = 0.0001);
Assert.DoesNotThrow(() => dist.Mean = 4);
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task NoRandomNumberGenerator01()
{
var dist = new FastRng.Double.Distributions.Exponential();
var dist = new FastRng.Double.Distributions.ExponentialLa5();
Assert.DoesNotThrowAsync(async () => await dist.GetDistributedValue());
Assert.That(await dist.GetDistributedValue(), Is.NaN);
}