Vector3 Vector3::randomInSphere(double radius, bool only_surface, RandomGenerator &random) {
// TODO More uniform spatial repartition
// The current randomization clusters result near the center and at the poles
VectorSpherical vec = {only_surface ? radius : random.genDouble() * radius, (random.genDouble() - 0.5) * Maths::PI,
random.genDouble() * Maths::TWOPI};
return Vector3(vec);
}
string FractalNoise::checkDistribution() {
stringstream result;
double val, min, max, mean;
RandomGenerator random;
int samples = 10000000;
double factor = 1.0 / to_double(samples);
min = 0.0;
max = 0.0;
mean = 0.0;
for (int i = 0; i < samples; i++) {
val = getBase1d((random.genDouble() - 0.5) * 10.0);
min = std::min(val, min);
max = std::max(val, max);
mean += val * factor;
}
result << "1d : min=" << min << " max=" << max << " mean=" << mean << endl;
min = 0.0;
max = 0.0;
mean = 0.0;
for (int i = 0; i < samples; i++) {
val = getBase2d((random.genDouble() - 0.5) * 10.0, (random.genDouble() - 0.5) * 10.0);
min = std::min(val, min);
max = std::max(val, max);
mean += val * factor;
}
result << "2d : min=" << min << " max=" << max << " mean=" << mean << endl;
min = 0.0;
max = 0.0;
mean = 0.0;
for (int i = 0; i < samples; i++) {
val = getBase3d((random.genDouble() - 0.5) * 10.0, (random.genDouble() - 0.5) * 10.0,
(random.genDouble() - 0.5) * 10.0);
min = std::min(val, min);
max = std::max(val, max);
mean += val * factor;
}
result << "3d : min=" << min << " max=" << max << " mean=" << mean << endl;
return result.str();
}
