public Item GenerateItem() { var rnd = genItemDistribution.Sample(); if (rnd >= 0 && rnd < 1) { return(GenerateFood()); } else if (rnd >= -1 && rnd < 0) { return(GeneratePotion()); } else if (rnd < -1) { return(GenerateWeapon()); } else { return(GenerateArmor()); } }
public void CanSample() { var n = new Stable(1.0, 1.0, 1.0, 1.0); n.Sample(); }
/// <summary> /// Run example /// </summary> /// <a href="http://en.wikipedia.org/wiki/Stable_distribution">Stable distribution</a> public void Run() { // 1. Initialize the new instance of the Stable distribution class with parameters Alpha = 2.0, Beta = 0, Scale = 1, Location = 0. var stable = new Stable(2.0, 0, 1, 0); Console.WriteLine(@"1. Initialize the new instance of the Stable distribution class with parameters Alpha = {0}, Beta = {1}, Scale = {2}, Location = {3}", stable.Alpha, stable.Beta, stable.Scale, stable.Location); Console.WriteLine(); // 2. Distributuion properties: Console.WriteLine(@"2. {0} distributuion properties:", stable); // Cumulative distribution function Console.WriteLine(@"{0} - Сumulative distribution at location '0.3'", stable.CumulativeDistribution(0.3).ToString(" #0.00000;-#0.00000")); // Probability density Console.WriteLine(@"{0} - Probability density at location '0.3'", stable.Density(0.3).ToString(" #0.00000;-#0.00000")); // Log probability density Console.WriteLine(@"{0} - Log probability density at location '0.3'", stable.DensityLn(0.3).ToString(" #0.00000;-#0.00000")); // Largest element in the domain Console.WriteLine(@"{0} - Largest element in the domain", stable.Maximum.ToString(" #0.00000;-#0.00000")); // Smallest element in the domain Console.WriteLine(@"{0} - Smallest element in the domain", stable.Minimum.ToString(" #0.00000;-#0.00000")); // Mean Console.WriteLine(@"{0} - Mean", stable.Mean.ToString(" #0.00000;-#0.00000")); // Median Console.WriteLine(@"{0} - Median", stable.Median.ToString(" #0.00000;-#0.00000")); // Mode Console.WriteLine(@"{0} - Mode", stable.Mode.ToString(" #0.00000;-#0.00000")); // Variance Console.WriteLine(@"{0} - Variance", stable.Variance.ToString(" #0.00000;-#0.00000")); // Standard deviation Console.WriteLine(@"{0} - Standard deviation", stable.StdDev.ToString(" #0.00000;-#0.00000")); // Skewness Console.WriteLine(@"{0} - Skewness", stable.Skewness.ToString(" #0.00000;-#0.00000")); Console.WriteLine(); // 3. Generate 10 samples of the Stable distribution Console.WriteLine(@"3. Generate 10 samples of the Stable distribution"); for (var i = 0; i < 10; i++) { Console.Write(stable.Sample().ToString("N05") + @" "); } Console.WriteLine(); Console.WriteLine(); // 4. Generate 100000 samples of the Stable(1) distribution and display histogram Console.WriteLine(@"4. Generate 100000 samples of the Stable(2, 0, 1, 0) distribution and display histogram"); var data = new double[100000]; Stable.Samples(data, 2, 0, 1, 0); ConsoleHelper.DisplayHistogram(data); Console.WriteLine(); // 5. Generate 100000 samples of the Stable(1, 0, 1, 0) distribution and display histogram Console.WriteLine(@"5. Generate 100000 samples of the Stable(1, 0, 1, 0) distribution and display histogram"); Stable.Samples(data, 1, 0, 1, 0); ConsoleHelper.DisplayHistogram(data); Console.WriteLine(); // 6. Generate 100000 samples of the Stable(1.5, 1, 1, 5) distribution and display histogram Console.WriteLine(@"6. Generate 100000 samples of the Stable(1.5, 1, 1, 5) distribution and display histogram"); Stable.Samples(data, 1.5, 1, 1, 5); ConsoleHelper.DisplayHistogram(data); }
public void CanSample() { var n = new Stable(1.0, 1.0, 1.0, 1.0); n.Sample(); }