using NumSharp.Core.Extensions;

using System;

using System.Collections.Generic;

using System.Text;

namespace NumSharp.Core

{

public class NDArrayRandom

{

public static int Seed { get; set; }

/// <summary>

/// Return a sample (or samples) from the “standard normal” distribution.

/// </summary>

/// <param name="size"></param>

/// <returns></returns>

public NDArray<double> randn(params int[] size)

{

return this.stardard_normal(size);

}

/// <summary>

/// Draw random samples from a normal (Gaussian) distribution.

/// </summary>

/// <param name="loc">Mean of the distribution</param>

/// <param name="scale">Standard deviation of the distribution</param>

/// <param name="size"></param>

/// <returns></returns>

public NDArray<double> normal(double loc, double scale, params int[] size)

{

if (size.Length == 0)

throw new Exception("d cannot be empty.");

NDArray<double> array = new NDArray<double>();

Random rand = new Random(); //reuse this if you are generating many

array.Shape = new Shape(size);

array.Data = new double[array.Shape.Size];

for (int i = 0; i < array.Shape.Size; i++)

{

double u1 = 1.0 - rand.NextDouble(); //uniform(0,1] random doubles

double u2 = 1.0 - rand.NextDouble();

double randStdNormal = Math.Sqrt(-2.0 * Math.Log(u1)) *

Math.Sin(2.0 * Math.PI * u2); //random normal(0,1)

double randNormal = loc + scale * randStdNormal; //random normal(mean,stdDev^2)

array.Data[i] = randNormal;

}

return array;

}

/// <summary>

/// Draw samples from a standard Normal distribution (mean=0, stdev=1).

/// </summary>

/// <param name="size"></param>

/// <returns></returns>

public NDArray<double> stardard_normal(params int[] size)

{

return this.normal(0, 1.0, size);

}

}

}