public void SampleStandard()
{
for (int i = 0; i < __loops; i++)
{
ZigguratGaussian.Sample(_rng);
}
}
/// <summary>
/// Genetic mutation for auxiliary argument data.
/// </summary>
public void MutateAuxArgs(double[] auxArgs, IRandomSource rng, double connectionWeightRange)
{
// Mutate centre.
// Add Gaussian distribution sample and clamp result to +-connectionWeightRange.
double tmp = auxArgs[0] + ZigguratGaussian.Sample(rng, 0, _auxArgsMutationSigmaCenter);
if (tmp < -connectionWeightRange)
{
auxArgs[0] = -connectionWeightRange;
}
else if (tmp > connectionWeightRange)
{
auxArgs[0] = connectionWeightRange;
}
else
{
auxArgs[0] = tmp;
}
// Mutate radius.
// Add Gaussian distribution sample and clamp result to [0,1]
tmp = auxArgs[1] + ZigguratGaussian.Sample(rng, 0, _auxArgsMutationSigmaCenter);
if (tmp < 0.0)
{
auxArgs[1] = 0.0;
}
else if (tmp > 1.0)
{
auxArgs[1] = 1.0;
}
else
{
auxArgs[1] = tmp;
}
}
// --- Methods manipulating CheckResults
public static void InitializeCheckResults()
{
Mod.Log.Info?.Write($"Initializing a new random buffer of size:{ResultsToPrecalcuate}");
Xoshiro256PlusRandomBuilder builder = new Xoshiro256PlusRandomBuilder();
IRandomSource rng = builder.Create();
double mean = Mod.Config.Probability.Mu;
double stdDev = Mod.Config.Probability.Sigma;
ZigguratGaussian.Sample(rng, mean, stdDev, CheckResults);
CheckResultIdx = 0;
}
public double SampleStandard()
{
double sum = 0f;
for (int i = 0; i < __loops; i++)
{
sum += ZigguratGaussian.Sample(_rng);
}
return(sum);
}
public void TestSampleBounds()
{
Xoshiro256PlusRandomBuilder builder = new Xoshiro256PlusRandomBuilder();
IRandomSource rng = builder.Create();
double mean = 0;
double stdDev = 4;
double[] sampleBuf = new double[4096];
ZigguratGaussian.Sample(rng, mean, stdDev, sampleBuf);
Dictionary <int, int> frequency = new Dictionary <int, int>();
foreach (double sample in sampleBuf)
{
int normalizedVal = 0;
if (sample > 0)
{
normalizedVal = (int)Math.Floor(sample);
}
else if (sample < 0)
{
normalizedVal = (int)Math.Ceiling(sample);
}
if (frequency.ContainsKey(normalizedVal))
{
frequency[normalizedVal] = frequency[normalizedVal] + 1;
}
else
{
frequency[normalizedVal] = 1;
}
}
List <int> orderedKeys = frequency.OrderByDescending(kvp => kvp.Key)
.Select(kvp => kvp.Key)
.ToList();
foreach (int key in orderedKeys)
{
Console.WriteLine($"Value:{key} had frequency:{frequency[key]}");
}
}
public void TestTimeFor4096()
{
Xoshiro256PlusRandomBuilder builder = new Xoshiro256PlusRandomBuilder();
IRandomSource rng = builder.Create();
double mean = 0;
double stdDev = 4;
double[] sampleBuf = new double[8172];
Stopwatch timer = new Stopwatch();
for (int i = 0; i < 10; i++)
{
timer.Start();
ZigguratGaussian.Sample(rng, mean, stdDev, sampleBuf);
timer.Stop();
Console.WriteLine($"Execution took: {timer.Elapsed} to generate 8172 elements.");
timer.Reset();
}
}
/// <summary>
/// Gets a variable from the Gaussian distribution with the provided mean and standard deviation.
/// </summary>
public double SampleGaussianDistribution(double mu, double sigma)
{
return(ZigguratGaussian.Sample(_rng, mu, sigma));
}
