Added exponential distributions

FastRng/Double/Distributions/Exponential.cs

@@ -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));
-        }
-    }
-}

FastRng/Double/Distributions/ExponentialLa10.cs

@@ -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);
+        }
+    }
+}

FastRng/Double/Distributions/ExponentialLa5.cs

@@ -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);
+        }
+    }
+}

FastRngTests/Double/Distributions/ExponentialLa10.cs

@@ -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);
+        }
+    }
+}

FastRngTests/Double/Distributions/ExponentialLa5.cs

@@ -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;
+            var dist = new FastRng.Double.Distributions.ExponentialLa5();
-            const double VARIANCE = MEAN * MEAN;
+            var fqa = new FrequencyAnalysis();
-            
-            var dist = new FastRng.Double.Distributions.Exponential{ Mean = MEAN };
-            var stats = new RunningStatistics();
             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($"mean={MEAN} vs. {stats.Mean}");
+            var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
-            TestContext.WriteLine($"variance={VARIANCE} vs {stats.Variance}");
 
-            Assert.That(stats.Mean, Is.EqualTo(MEAN).Within(0.1), "Mean is out of range");
+            Assert.That(result[0], Is.EqualTo(1.0002177398625).Within(0.05));
-            Assert.That(stats.Variance, Is.EqualTo(VARIANCE).Within(0.1), "Variance is out of range");
+            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);
         }