/// <summary> /// Initializes a new instance from an existing one (copy constructor). /// </summary> /// <param name="original">The original <see cref="UniformDistributedRandom"/> instance which is used to initialize the new instance.</param> /// <param name="cloner">A <see cref="Cloner"/> which is used to track all already cloned objects in order to avoid cycles.</param> private UniformDistributedRandom(UniformDistributedRandom original, Cloner cloner) : base(original, cloner) { uniform = cloner.Clone(original.uniform); min = original.min; max = original.max; }
public override IEnumerable<IDataDescriptor> GetDataDescriptors() { var sizes = new int[] { 50, 100, 200 }; var pp = new double[] { 0.1, 0.25, 0.5 }; var noiseRatios = new double[] { 0.01, 0.05, 0.1, 0.2 }; var mt = new MersenneTwister(); var xGenerator = new NormalDistributedRandom(mt, 0, 1); var weightGenerator = new UniformDistributedRandom(mt, 0, 10); return (from size in sizes from p in pp from noiseRatio in noiseRatios select new FeatureSelection(size, p, noiseRatio, xGenerator, weightGenerator)) .Cast<IDataDescriptor>() .ToList(); }
/// <summary> /// Generates a new double random number. /// </summary> /// <returns>A double random number.</returns> public double NextDouble() { return(UniformDistributedRandom.NextDouble(uniform, min, max)); }
/// <summary> /// Initializes a new instance from an existing one (copy constructor). /// </summary> /// <param name="original">The original <see cref="UniformDistributedRandom"/> instance which is used to initialize the new instance.</param> /// <param name="cloner">A <see cref="Cloner"/> which is used to track all already cloned objects in order to avoid cycles.</param> private UniformDistributedRandom(UniformDistributedRandom original, Cloner cloner) : base(original, cloner) { uniform = cloner.Clone(original.uniform); min = original.min; max = original.max; }