Migrated weibull distribution to shape fitter

FastRng/Double/Distributions/Weibull.cs

@@ -1,47 +0,0 @@
-using System;
-using System.Threading;
-using System.Threading.Tasks;
-
-namespace FastRng.Double.Distributions
-{
-    public sealed class Weibull : IDistribution
-    {
-        private double shape = 1.0;
-        private double scale = 1.0;
-
-        public IRandom Random { get; set; }
-
-        public double Shape
-        {
-            get => this.shape;
-            set
-            {
-                if(value <= 0.0)
-                    throw new ArgumentOutOfRangeException(message: "Shape must be greater than 0", null);
-                
-                this.shape = value;
-            }
-        }
-
-        public double Scale
-        {
-            get => this.scale;
-            set
-            {
-                if(value <= 0.0)
-                    throw new ArgumentOutOfRangeException(message: "Scale must be greater than 0", null);
-                
-                this.scale = value;
-            }
-        }
-
-        public async ValueTask<double> GetDistributedValue(CancellationToken token = default)
-        {
-            if (this.Random == null)
-                return double.NaN;
-
-            var value = await this.Random.GetUniform(token);
-            return this.Scale * Math.Pow(-Math.Log(value), 1.0 / this.Shape);
-        }
-    }
-}

FastRng/Double/Distributions/WeibullK05La1.cs

@@ -0,0 +1,36 @@
+using System;
+using System.Threading;
+using System.Threading.Tasks;
+
+namespace FastRng.Double.Distributions
+{
+    public sealed class WeibullK05La1 : IDistribution
+    {
+        private const double K = 0.5;
+        private const double LAMBDA = 1.0;
+        private const double CONSTANT = 0.221034183615129;
+
+        private ShapeFitter fitter;
+        private IRandom random;
+
+        public IRandom Random
+        {
+            get => this.random;
+            set
+            {
+                this.random = value;
+                this.fitter = new ShapeFitter(WeibullK05La1.ShapeFunction, this.random, 100);
+            }
+        }
+        
+        private static double ShapeFunction(double x) => CONSTANT * ( (K / LAMBDA) * Math.Pow(x / LAMBDA, K - 1.0d) * Math.Exp(-Math.Pow(x/LAMBDA, K)));
+
+        public async ValueTask<double> GetDistributedValue(CancellationToken token = default)
+        {
+            if (this.Random == null)
+                return double.NaN;
+            
+            return await this.fitter.NextNumber(token);
+        }
+    }
+}

FastRngTests/Double/Distributions/WeibullK05La1.cs

@@ -8,31 +8,40 @@ using NUnit.Framework;
 namespace FastRngTests.Double.Distributions
 {
     [ExcludeFromCodeCoverage]
-    public class Weibull
+    public class WeibullK05La1
     {
         [Test]
         [Category(TestCategories.COVER)]
         [Category(TestCategories.NORMAL)]
         public async Task TestWeibullDistribution01()
         {
-            const double SHAPE = 2;
+            var dist = new FastRng.Double.Distributions.WeibullK05La1();
-            const double SCALE = 3;
+            var fra = new FrequencyAnalysis();
-            const double VARIANCE = 9 * (1 - Math.PI / 4);
-            var mean = 3 * Math.Sqrt(Math.PI) / 2;
-
-            var dist = new FastRng.Double.Distributions.Weibull{ Shape = SHAPE, Scale = SCALE };
-            var stats = new RunningStatistics();
             var rng = new MultiThreadedRng();
             
             for (var n = 0; n < 100_000; n++)
-                stats.Push(await rng.NextNumber(dist));
+                fra.CountThis(await rng.NextNumber(dist));
             
             rng.StopProducer();
-            TestContext.WriteLine($"mean={mean} vs. {stats.Mean}");
+            var result = fra.NormalizeAndPlotEvents(TestContext.WriteLine);
-            TestContext.WriteLine($"variance={VARIANCE} vs {stats.Variance}");
 
-            Assert.That(stats.Mean, Is.EqualTo(mean).Within(0.2), "Mean is out of range");
+            Assert.That(result[0], Is.EqualTo(1.000000000).Within(0.2));
-            Assert.That(stats.Variance, Is.EqualTo(VARIANCE).Within(0.2), "Variance is out of range");
+            Assert.That(result[1], Is.EqualTo(0.678415772).Within(0.09));
+            Assert.That(result[2], Is.EqualTo(0.536595233).Within(0.09));
+            
+            Assert.That(result[21], Is.EqualTo(0.147406264).Within(0.01));
+            Assert.That(result[22], Is.EqualTo(0.142654414).Within(0.01));
+            Assert.That(result[23], Is.EqualTo(0.138217760).Within(0.01));
+            
+            Assert.That(result[50], Is.EqualTo(0.075769787).Within(0.095));
+            
+            Assert.That(result[75], Is.EqualTo(0.053016799).Within(0.05));
+            Assert.That(result[85], Is.EqualTo(0.047144614).Within(0.05));
+            Assert.That(result[90], Is.EqualTo(0.044629109).Within(0.05));
+            
+            Assert.That(result[97], Is.EqualTo(0.041484591).Within(0.05));
+            Assert.That(result[98], Is.EqualTo(0.041067125).Within(0.05));
+            Assert.That(result[99], Is.EqualTo(0.040656966).Within(0.05));
         }
         
         [Test]
@@ -41,9 +50,10 @@ namespace FastRngTests.Double.Distributions
         public async Task TestWeibullGeneratorWithRange01()
         {
             var rng = new MultiThreadedRng();
+            var dist = new FastRng.Double.Distributions.WeibullK05La1();
             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.Weibull());
+                samples[n] = await rng.NextNumber(-1.0, 1.0, dist);
             
             rng.StopProducer();
             Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0), "Min out of range");
@@ -56,9 +66,10 @@ namespace FastRngTests.Double.Distributions
         public async Task TestWeibullGeneratorWithRange02()
         {
             var rng = new MultiThreadedRng();
+            var dist = new FastRng.Double.Distributions.WeibullK05La1();
             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.Weibull());
+                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");
@@ -71,7 +82,7 @@ namespace FastRngTests.Double.Distributions
         public async Task TestWeibullGeneratorWithRange03()
         {
             var rng = new MultiThreadedRng();
-            var dist = new FastRng.Double.Distributions.Weibull { Random = rng }; // Test default parameters
+            var dist = new FastRng.Double.Distributions.WeibullK05La1 { Random = rng }; // Test default parameters
             
             var samples = new double[1_000];
             for (var n = 0; n < samples.Length; n++)
@@ -82,30 +93,12 @@ 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.Weibull();
-            
-            Assert.Throws<ArgumentOutOfRangeException>(() => dist.Scale = 0);
-            Assert.Throws<ArgumentOutOfRangeException>(() => dist.Scale = -78);
-            Assert.DoesNotThrow(() => dist.Scale = 0.0001);
-            Assert.DoesNotThrow(() => dist.Scale = 4);
-            
-            Assert.Throws<ArgumentOutOfRangeException>(() => dist.Shape = 0);
-            Assert.Throws<ArgumentOutOfRangeException>(() => dist.Shape = -78);
-            Assert.DoesNotThrow(() => dist.Shape = 0.0001);
-            Assert.DoesNotThrow(() => dist.Shape = 4);
-        }
-
         [Test]
         [Category(TestCategories.COVER)]
         [Category(TestCategories.NORMAL)]
         public async Task NoRandomNumberGenerator01()
         {
-            var dist = new FastRng.Double.Distributions.Weibull();
+            var dist = new FastRng.Double.Distributions.WeibullK05La1();
             Assert.DoesNotThrowAsync(async () => await dist.GetDistributedValue());
             Assert.That(await dist.GetDistributedValue(), Is.NaN);
         }