/// <summary>
/// Initializes a new instance of the <see cref="MultivariateNormalSampler"/> class.
/// </summary>
/// <param name="engine">
/// The simulation engine to be used for sampling.
/// </param>
/// <param name="mean">
/// The mean values of the variables to be generated simultaneously.
/// </param>
/// <param name="choleskyFactor">
/// The Cholesky factorization of a matrix defining the desired joint distribution.
/// </param>
private MultivariateNormalSampler(IRandomNumberEngine engine, double[] mean, double[] choleskyFactor)
{
this.Length = mean.Length;
this.mean = mean;
this.choleskyFactor = choleskyFactor;
this.standardNormalSampler = new StandardNormalSampler(engine);
this.buffer = new double[this.mean.Length];
}
public void TestFill()
{
var sampler1 = new StandardNormalSampler(new ReducedThreeFry4X64(1));
var actual = Enumerable.Repeat(sampler1, 10).Select(x => x.GetNext()).ToArray();
var sampler2 = new StandardNormalSampler(new ReducedThreeFry4X64(1));
var expected = new double[10];
sampler2.Fill(expected);
Assert.AreEqual(expected, actual);
}
public void TestConstructInvalid()
{
Assert.Throws <ArgumentNullException>(
() => _ = new StandardNormalSampler(null));
}
