public static Vector<Complex> GenerateRandomDenseVector(int order)
{
// Fill a matrix with standard random numbers.
var normal = new Distributions.Normal
{
RandomSource = new Random.MersenneTwister(1)
};
var v = new DenseVector(order);
for (var i = 0; i < order; i++)
{
v[i] = new Complex(normal.Sample(), normal.Sample());
}
// Generate a matrix which is positive definite.
return v;
}
public static Vector <Complex> GenerateRandomUserDefinedVector(int order)
{
// Fill a matrix with standard random numbers.
var normal = new Distributions.Normal
{
RandomSource = new Numerics.Random.MersenneTwister(1)
};
var v = new UserDefinedVector(order);
for (var i = 0; i < order; i++)
{
v[i] = new Complex(normal.Sample(), normal.Sample());
}
// Generate a matrix which is positive definite.
return(v);
}
public static Matrix<Complex> GenerateRandomDenseMatrix(int row, int col)
{
// Fill a matrix with standard random numbers.
var normal = new Distributions.Normal
{
RandomSource = new Random.MersenneTwister(1)
};
var matrixA = new DenseMatrix(row, col);
for (var i = 0; i < row; i++)
{
for (var j = 0; j < col; j++)
{
matrixA[i, j] = new Complex(normal.Sample(), normal.Sample());
}
}
// Generate a matrix which is positive definite.
return matrixA;
}
public static Matrix <Complex> GenerateRandomDenseMatrix(int row, int col)
{
// Fill a matrix with standard random numbers.
var normal = new Distributions.Normal
{
RandomSource = new Numerics.Random.MersenneTwister(1)
};
var matrixA = new DenseMatrix(row, col);
for (var i = 0; i < row; i++)
{
for (var j = 0; j < col; j++)
{
matrixA[i, j] = new Complex(normal.Sample(), normal.Sample());
}
}
// Generate a matrix which is positive definite.
return(matrixA);
}
public static Matrix <Complex> GenerateRandomPositiveDefiniteHermitianUserDefinedMatrix(int order)
{
// Fill a matrix with standard random numbers.
var normal = new Distributions.Normal
{
RandomSource = new Numerics.Random.MersenneTwister(1)
};
var matrixA = new UserDefinedMatrix(order);
for (var i = 0; i < order; i++)
{
for (var j = 0; j < order; j++)
{
matrixA[i, j] = new Complex(normal.Sample(), normal.Sample());
}
}
// Generate a Hermitian matrix which is positive definite.
return(matrixA.ConjugateTranspose() * matrixA);
}
public static Vector <float> GenerateRandomDenseVector(int order)
{
// Fill a matrix with standard random numbers.
var normal = new Distributions.Normal();
normal.RandomSource = new Numerics.Random.MersenneTwister(1);
var v = new DenseVector(order);
for (int i = 0; i < order; i++)
{
v[i] = (float)normal.Sample();
}
// Generate a matrix which is positive definite.
return(v);
}
public static Matrix GenerateRandomDenseMatrix(int row, int col)
{
// Fill a matrix with standard random numbers.
var normal = new Distributions.Normal();
normal.RandomSource = new Random.MersenneTwister(1);
var A = new DenseMatrix(row, col);
for (int i = 0; i < row; i++)
{
for (int j = 0; j < col; j++)
{
A[i, j] = normal.Sample();
}
}
// Generate a matrix which is positive definite.
return A;
}
public static Matrix GenerateRandomPositiveDefiniteMatrix(int order)
{
// Fill a matrix with standard random numbers.
var normal = new Distributions.Normal();
normal.RandomSource = new Random.MersenneTwister(1);
var A = new DenseMatrix(order);
for (int i = 0; i < order; i++)
{
for (int j = 0; j < order; j++)
{
A[i, j] = normal.Sample();
}
}
// Generate a matrix which is positive definite.
return A.Transpose() * A;
}
public static Matrix <float> GenerateRandomPositiveDefiniteUserDefinedMatrix(int order)
{
// Fill a matrix with standard random numbers.
var normal = new Distributions.Normal();
normal.RandomSource = new Numerics.Random.MersenneTwister(1);
var matrixA = new UserDefinedMatrix(order);
for (int i = 0; i < order; i++)
{
for (int j = 0; j < order; j++)
{
matrixA[i, j] = (float)normal.Sample();
}
}
// Generate a matrix which is positive definite.
return(matrixA.Transpose() * matrixA);
}
public static Matrix <double> GenerateRandomUserDefinedMatrix(int row, int col)
{
// Fill a matrix with standard random numbers.
var normal = new Distributions.Normal();
normal.RandomSource = new Numerics.Random.MersenneTwister(1);
var matrixA = new UserDefinedMatrix(row, col);
for (int i = 0; i < row; i++)
{
for (int j = 0; j < col; j++)
{
matrixA[i, j] = normal.Sample();
}
}
// Generate a matrix which is positive definite.
return(matrixA);
}
public static Vector GenerateRandomUserDefinedVector(int order)
{
// Fill a matrix with standard random numbers.
var normal = new Distributions.Normal();
normal.RandomSource = new Random.MersenneTwister(1);
var v = new UserDefinedVector(order);
for (int i = 0; i < order; i++)
{
v[i] = normal.Sample();
}
// Generate a matrix which is positive definite.
return v;
}
public static Matrix<Complex> GenerateRandomPositiveDefiniteHermitianDenseMatrix(int order)
{
// Fill a matrix with standard random numbers.
var normal = new Distributions.Normal
{
RandomSource = new Random.MersenneTwister(1)
};
var matrixA = new DenseMatrix(order);
for (var i = 0; i < order; i++)
{
for (var j = 0; j < order; j++)
{
matrixA[i, j] = new Complex(normal.Sample(), normal.Sample());
}
}
// Generate a Hermitian matrix which is positive definite.
return matrixA.ConjugateTranspose() * matrixA;
}