Alex Herbert created RNG-129:
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Summary: Performance improvement for UnitSphereSampler
Key: RNG-129
URL: https://issues.apache.org/jira/browse/RNG-129
Project: Commons RNG
Issue Type: Improvement
Components: sampling
Affects Versions: 1.3
Reporter: Alex Herbert
The UnitSphereSampler accepts a dimension argument and creates the sample using
iteration over an array of the given dimension creating n Gaussian samples.
This can be optimised for low order dimensions to remove the use of array
iteration, e.g.
{code:java}
final double[] v = new double[dimension];
double sum = 0;
for (int i = 0; i < dimension; i++) {
final double x = sampler.sample();
v[i] = x;
sum += x * x;
}
{code}
becomes for 3D:
{code:java}
final double x = sampler.sample();
final double y = sampler.sample();
final double z = sampler.sample();
final double sum = x * x + y * y + z * z;
{code}
The special case of 1D sampling can be handled by returning either 1 or -1 in a
vector based on a single bit of the random source.
Optimised versions can be created by adding a factory method to the class:
{code:java}
public static UnitSphereSampler.of(int dimension, UniformRandomProvider rng) {
// ...
}
{code}
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