/// <summary>
/// Genetic mutation for auxiliary argument data.
/// </summary>
public void MutateAuxArgs(double[] auxArgs, IRandomSource rng, ZigguratGaussianDistribution gaussianSampler, double connectionWeightRange)
{
// Mutate centre.
// Add Gaussian distribution sample and clamp result to +-connectionWeightRange.
double tmp = auxArgs[0] + gaussianSampler.Sample(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] + gaussianSampler.Sample(0, _auxArgsMutationSigmaRadius);
if (tmp < 0.0)
{
auxArgs[1] = 0.0;
}
else if (tmp > 1.0)
{
auxArgs[1] = 1.0;
}
else
{
auxArgs[1] = tmp;
}
}
public FunctionBenchmarks()
{
// Create some random Gaussian values as the inputs to the activation functions.
ZigguratGaussianDistribution gaussian = new ZigguratGaussianDistribution(0);
for (int i = 0; i < _x.Length; i++)
{
_x[i] = gaussian.Sample(0, 2.0);
_f[i] = (float)gaussian.Sample(0, 2.0);
}
}
public BenchmarksVectorizedDouble()
{
// Create some random Gaussian values as the inputs to the activation functions.
var gaussian = new ZigguratGaussianDistribution(0);
for (int i = 0; i < _x.Length; i++)
{
_x[i] = gaussian.Sample(0, 2.0);
}
}