Initial

FastRng/Distributions/Exponential.cs

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+using System;
+using System.Threading;
+using System.Threading.Tasks;
+
+namespace FastRng.Distributions
+{
+    public sealed class Exponential : IDistribution
+    {
+        private double mean = 1;
+        
+        public IRandom Random { get; set; }
+
+        public double Mean
+        {
+            get => this.mean;
+            set
+            {
+                if(value <= 0)
+                    throw new ArgumentOutOfRangeException(message: "Mean must be greater than 0", null);
+                
+                this.mean = value;
+            }
+        }
+
+        public async Task<double> GetDistributedValue(CancellationToken token)
+        {
+            if (this.Random == null)
+                return 0;
+
+            if(this.Mean == 1)
+                return -Math.Log(await this.Random.GetUniformDouble(token));
+            else
+                return this.Mean * -Math.Log(await this.Random.GetUniformDouble(token));
+        }
+    }
+}

FastRng/Distributions/Gamma.cs

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+using System;
+using System.Threading;
+using System.Threading.Tasks;
+
+namespace FastRng.Distributions
+{
+    public sealed class Gamma : IDistribution
+    {
+        private double shape = 1;
+        
+        public IRandom Random { get; set; }
+
+        public double Shape
+        {
+            get => this.shape;
+            set
+            {
+                if(value <= 0)
+                    throw new ArgumentOutOfRangeException(message: "Shape must be greater than 0", null);
+                
+                this.shape = value;
+            }
+        }
+
+        public double Scale { get; set; } = 1;
+        
+        public async Task<double> GetDistributedValue(CancellationToken token)
+        {
+            if (this.Random == null)
+                return 0;
+            
+            // Implementation based on "A Simple Method for Generating Gamma Variables"
+            // by George Marsaglia and Wai Wan Tsang.  ACM Transactions on Mathematical Software
+            // Vol 26, No 3, September 2000, pages 363-372.
+            
+            if (shape >= 1.0)
+            {
+                var distNormal = new Normal();
+                var d = shape - 1.0 / 3.0;
+                var c = 1.0 / Math.Sqrt(9.0 * d);
+                while(true)
+                {
+                    double x, v;
+                    do
+                    {
+                        x = await this.Random.NextNumber(0, 1, distNormal, token);
+                        v = 1.0 + c * x;
+                    }
+                    while (v <= 0.0);
+                    
+                    v = v * v * v;
+                    var u = await this.Random.GetUniformDouble(token);
+                    var xSquared = x * x;
+                    
+                    if (u < 1.0 - 0.0331 * xSquared * xSquared || Math.Log(u) < 0.5 * xSquared + d * (1.0 - v + Math.Log(v)))
+                        return this.Scale * d * v;
+                }
+            }
+            else
+            {
+                var dist = new Gamma{ Scale = 1, Shape = 1 + this.Shape};
+                
+                var g = await this.Random.NextNumber(0.0f, 1.0f, dist, token); // TODO: Use double
+                var w = await this.Random.GetUniformDouble(token);
+                return this.Scale * g * Math.Pow(w, 1.0 / this.Shape);
+            }
+        }
+    }
+}

FastRng/Distributions/Normal.cs

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+using System;
+using System.Threading;
+using System.Threading.Tasks;
+
+namespace FastRng.Distributions
+{
+    public sealed class Normal : IDistribution
+    {
+        private double standardDeviation = 1;
+        
+        public IRandom Random { get; set; }
+
+        public double Mean { get; set; } = 0;
+
+        public double StandardDeviation
+        {
+            get => this.standardDeviation;
+            set
+            {
+                if(value <= 0)
+                    throw new ArgumentOutOfRangeException(message: "Standard deviation must be greater than 0", null);
+                
+                this.standardDeviation = value;
+            }
+        }
+
+        public async Task<double> GetDistributedValue(CancellationToken token = default)
+        {
+            if (this.Random == null)
+                return 0;
+
+            var u1 = await this.Random.GetUniformDouble(token);
+            var u2 = await this.Random.GetUniformDouble(token);
+            var r = Math.Sqrt(-2.0 * Math.Log(u1));
+            var theta = 2.0 * Math.PI * u2;
+            var value = r * Math.Sin(theta);
+
+            return this.Mean + this.StandardDeviation * value;
+        }
+    }
+}

FastRng/Distributions/Uniform.cs

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+using System.Threading;
+using System.Threading.Tasks;
+
+namespace FastRng.Distributions
+{
+    public sealed class Uniform : IDistribution
+    {
+        public IRandom Random { get; set; }
+        
+        public async Task<double> GetDistributedValue(CancellationToken token = default) => this.Random == null ? 0 : await this.Random.GetUniformDouble(token);
+    }
+}