/**
* <p>
* Creates a new vector which is drawn from a multivariate normal distribution with zero mean
* and the provided covariance.
* </p>
*
* @see CovarianceRandomDraw_DDRM
*
* @param covariance Covariance of the multivariate normal distribution
* @return Vector randomly drawn from the distribution
*/
public static SimpleMatrix <T> randomNormal(SimpleMatrix <T> covariance, IMersenneTwister random)
{
SimpleMatrix <T> found = new SimpleMatrix <T>(covariance.numRows(), 1);
var m = covariance.getMatrix();
var bits = covariance.bits();
if (bits == 64)
{
// Check type here to make sure
if (typeof(T) != typeof(DMatrixRMaj))
{
throw new InvalidOperationException("This operation is only valid for type DMatrixRMaj.");
}
var draw = new CovarianceRandomDraw_DDRM(random, m as DMatrixRMaj);
draw.next(found.getMatrix() as DMatrixRMaj);
}
else if (bits == 32)
{
// Check type here to make sure
if (typeof(T) != typeof(FMatrixRMaj))
{
throw new InvalidOperationException("This operation is only valid for type FMatrixRMaj.");
}
var draw = new CovarianceRandomDraw_FDRM(random, m as FMatrixRMaj);
draw.next(found.getMatrix() as FMatrixRMaj);
}
else // Unknown data type
{
throw new InvalidOperationException("Unknown data type: must be double (64 bits) or float (32 bits).");
}
return(found);
}
/// <summary>
/// <para>
/// Creates a new vector which is drawn from a multivariate normal distribution with zero mean
/// and the provided covariance.
/// </para>
/// </summary>
/// <param name="covariance"> Covariance of the multivariate normal distribution </param>
/// <returns> Vector randomly drawn from the distribution </returns>
/// <seealso cref= CovarianceRandomDraw_DDRM </seealso>
public static SimpleMatrix <W> randomNormal(SimpleMatrix <W> covariance, Random random)
{
SimpleMatrix <W> found = new SimpleMatrix <W>(covariance.numRows(), 1, covariance.getType());
switch (found.getType().tipo)
{
case Types.DDRM:
{
CovarianceRandomDraw_DDRM draw = new CovarianceRandomDraw_DDRM(random, (DMatrixRMaj)covariance.mat);
draw.next((DMatrixRMaj)found.mat);
}
break;
//case MatrixType.FDRM:
// {
// CovarianceRandomDraw_FDRM draw = new CovarianceRandomDraw_FDRM(random, (FMatrixRMaj)covariance.Matrix);
// draw.next((FMatrixRMaj)found.mat);
// }
// break;
default:
throw new System.ArgumentException("Matrix type is currently not supported");
}
return(found);
}
/**
* <p>
* Creates a new vector which is drawn from a multivariate normal distribution with zero mean
* and the provided covariance.
* </p>
*
* @see CovarianceRandomDraw_DDRM
*
* @param covariance Covariance of the multivariate normal distribution
* @return Vector randomly drawn from the distribution
*/
public static SimpleMatrixD randomNormal(SimpleMatrixD covariance, IMersenneTwister random)
{
SimpleMatrixD found = new SimpleMatrixD(covariance.numRows(), 1);
var draw = new CovarianceRandomDraw_DDRM(random, covariance.getMatrix());
draw.next(found.getMatrix());
return(found);
}
