internal static void SamplesUnchecked(System.Random rnd, double[] values, double freedom)
{
// Use the simple method if the degrees of freedom is an integer anyway
if (Math.Floor(freedom) == freedom && freedom < int.MaxValue)
{
var n = (int)freedom;
var standard = new double[values.Length * n];
Normal.SamplesUnchecked(rnd, standard, 0.0, 1.0);
CommonParallel.For(0, values.Length, 4096, (a, b) =>
{
for (int i = a; i < b; i++)
{
int k = i * n;
double sum = 0;
for (int j = 0; j < n; j++)
{
sum += standard[k + j] * standard[k + j];
}
values[i] = Math.Sqrt(sum);
}
});
return;
}
// Call the gamma function (see http://en.wikipedia.org/wiki/Gamma_distribution#Specializations
// for a justification)
Gamma.SamplesUnchecked(rnd, values, freedom / 2.0, .5);
}
static void SamplesUnchecked(System.Random rnd, double[] values, double location, double scale, double freedom)
{
Gamma.SamplesUnchecked(rnd, values, 0.5 * freedom, 0.5);
for (int i = 0; i < values.Length; i++)
{
values[i] = Normal.Sample(rnd, location, scale * Math.Sqrt(freedom / values[i]));
}
}
static void SamplesUnchecked(System.Random rnd, double[] values, double shape, double scale)
{
Gamma.SamplesUnchecked(rnd, values, shape, scale);
CommonParallel.For(0, values.Length, 4096, (a, b) =>
{
for (int i = a; i < b; i++)
{
values[i] = 1.0 / values[i];
}
});
}
internal static void SamplesUnchecked(System.Random rnd, double[] values, double a, double b)
{
var y = new double[values.Length];
Gamma.SamplesUnchecked(rnd, values, a, 1.0);
Gamma.SamplesUnchecked(rnd, y, b, 1.0);
CommonParallel.For(0, values.Length, 4096, (aa, bb) =>
{
for (int i = aa; i < bb; i++)
{
values[i] = values[i] / (values[i] + y[i]);
}
});
}
/// <summary>
/// Fills an array with samples generated from the distribution.
/// </summary>
public void Samples(double[] values)
{
Gamma.SamplesUnchecked(_random, values, _shape, _rate);
}
static IEnumerable <double> SamplesUnchecked(System.Random rnd, double shape, double scale)
{
return(Gamma.SamplesUnchecked(rnd, shape, scale).Select(z => 1.0 / z));
}
