public static void GenerateSortedAndShuffleNPercent(SortingArray array, int chance)
{
GenerateSorted(array);
for (int i = 0; i < array.Length; i++)
{
StandardGenerator rand = new StandardGenerator();
int randNum = rand.Next(101);
if (randNum <= chance)
{
int pos = rand.Next(array.Length);
array.Swap(i, pos);
Updated(array);
}
}
}
/// <summary>
/// Generates a random vector of observations from the current distribution.
/// </summary>
///
/// <param name="samples">The number of samples to generate.</param>
///
/// <returns>A random vector of observations drawn from this distribution.</returns>
///
public double[][] Generate(int samples)
{
if (chol == null)
{
throw new NonPositiveDefiniteMatrixException("Covariance matrix is not positive definite.");
}
var r = new StandardGenerator(BestCS.Math.Tools.Random.Next());
double[,] A = chol.LeftTriangularFactor;
double[][] data = new double[samples][];
for (int i = 0; i < data.Length; i++)
{
double[] sample = new double[Dimension];
for (int j = 0; j < sample.Length; j++)
{
sample[j] = r.Next();
}
data[i] = A.Multiply(sample).Add(Mean);
}
return(data);
}
/// <summary>
/// Samples a value from the function given a input value.
/// </summary>
///
/// <param name="x">Function input value.</param>
///
/// <returns>
/// Draws a random value from the function.
/// </returns>
///
public double Generate(double x)
{
// assume zero-mean noise
double y = alpha * x + gaussian.Next();
if (y > range.Max)
{
y = range.Max;
}
else if (y < range.Min)
{
y = range.Min;
}
return(y);
}
public static void GenerateRandom(SortingArray array)
{
for (int i = 0; i < array.Length; i++)
{
StandardGenerator rand = new StandardGenerator();
int val = rand.Next(1, array.Length + 1);
array.Modify(i, val);
Updated(array);
}
}
public static void Shuffle(SortingArray array)
{
for (int i = 0; i < array.Length; i++)
{
StandardGenerator rand = new StandardGenerator();
int pos = rand.Next(0, array.Length);
array.Swap(i, pos);
Updated(array);
}
}
public static void GenerateRandomAscending(SortingArray array)
{
for (int i = 0; i < array.Length; i++)
{
StandardGenerator rand = new StandardGenerator();
int value = rand.Next(i, array.Length) + 1;
array.Modify(i, value);
Updated(array);
}
}
/// <summary>
/// Generates a random vector of observations from the current distribution.
/// </summary>
///
/// <returns>A random vector of observations drawn from this distribution.</returns>
///
public double[] Generate()
{
var r = new StandardGenerator(Accord.Math.Tools.Random.Next());
double[,] A = chol.LeftTriangularFactor;
double[] sample = new double[Dimension];
for (int j = 0; j < sample.Length; j++)
{
sample[j] = r.Next();
}
return(A.Multiply(sample).Add(Mean));
}
/// <summary>
/// Generates a random vector of observations from the current distribution.
/// </summary>
///
/// <returns>A random vector of observations drawn from this distribution.</returns>
///
public double[] Generate()
{
if (chol == null)
{
throw new NonPositiveDefiniteMatrixException("Covariance matrix is not positive definite.");
}
var r = new StandardGenerator(Accord.Math.Tools.Random.Next());
double[,] A = chol.LeftTriangularFactor;
double[] sample = new double[Dimension];
for (int j = 0; j < sample.Length; j++)
{
sample[j] = r.Next();
}
return(A.Multiply(sample).Add(Mean));
}
/// <summary>
/// Generates a random vector of observations from the current distribution.
/// </summary>
///
/// <param name="samples">The number of samples to generate.</param>
///
/// <returns>A random vector of observations drawn from this distribution.</returns>
///
public double[][] Generate(int samples)
{
var r = new StandardGenerator(Accord.Math.Tools.Random.Next());
double[,] A = chol.LeftTriangularFactor;
double[][] data = new double[samples][];
for (int i = 0; i < data.Length; i++)
{
double[] sample = new double[Dimension];
for (int j = 0; j < sample.Length; j++)
{
sample[j] = r.Next();
}
data[i] = A.Multiply(sample).Add(Mean);
}
return(data);
}
/// <summary>
/// Generate next random number.
/// </summary>
///
/// <returns>Returns next random number.</returns>
///
public float Next()
{
return((float)rand.Next() * stdDev + mean);
}
/// <summary>
/// Generate next random number.
/// </summary>
///
/// <returns>Returns next random number.</returns>
///
public double Next()
{
return(rand.Next() * stdDev + mean);
}