/// <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;
}