/**
* <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);
}
