org.joml.sampling.UniformSampling Maven / Gradle / Ivy
/*
* The MIT License
*
* Copyright (c) 2016-2019 JOML
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*/
package org.joml.sampling;
import org.joml.Random;
/**
* Generates uniform samples.
*
* @author Kai Burjack
*/
public class UniformSampling {
/**
* Generates uniform samples on a unit disk.
*
* @author Kai Burjack
*/
public static class Disk {
private final Random rnd;
/**
* Create a new instance of {@link Disk}, initialize the random number generator with the given seed and generate numSamples number of sample
* positions on the unit disk, and call the given callback for each sample generate.
*
* @param seed
* the seed to initialize the random number generator with
* @param numSamples
* the number of samples to generate
* @param callback
* will be called for each sample generated
*/
public Disk(long seed, int numSamples, Callback2d callback) {
this.rnd = new Random(seed);
generate(numSamples, callback);
}
private void generate(int numSamples, Callback2d callback) {
for (int i = 0; i < numSamples; i++) {
float r = rnd.nextFloat();
float a = rnd.nextFloat() * 2.0f * (float) Math.PI;
float sqrtR = (float) Math.sqrt(r);
float x = sqrtR * (float) Math.sin_roquen_9(a + 0.5 * Math.PI);
float y = sqrtR * (float) Math.sin_roquen_9(a);
callback.onNewSample(x, y);
}
}
}
/**
* Generates uniform samples on a unit sphere.
*
* @author Kai Burjack
*/
public static class Sphere {
private final Random rnd;
/**
* Create a new instance of {@link Sphere}, initialize the random number generator with the given seed and generate numSamples number of sample
* positions on the unit sphere, and call the given callback for each sample generate.
*
* @param seed
* the seed to initialize the random number generator with
* @param numSamples
* the number of samples to generate
* @param callback
* will be called for each sample generated
*/
public Sphere(long seed, int numSamples, Callback3d callback) {
this.rnd = new Random(seed);
generate(numSamples, callback);
}
/**
* Create numSamples number of samples which are uniformly distributed on a unit sphere, and call the given callback for each sample generated.
*
* Reference: http://mathworld.wolfram.com/
*
* @param numSamples
* the number of samples to generate
* @param callback
* will be called for each sample generated
*/
public void generate(int numSamples, Callback3d callback) {
for (int i = 0; i < numSamples;) {
float x1 = rnd.nextFloat() * 2.0f - 1.0f;
float x2 = rnd.nextFloat() * 2.0f - 1.0f;
if (x1 * x1 + x2 * x2 >= 1.0f)
continue;
float sqrt = (float) Math.sqrt(1.0 - x1 * x1 - x2 * x2);
float x = 2 * x1 * sqrt;
float y = 2 * x2 * sqrt;
float z = 1.0f - 2.0f * (x1 * x1 + x2 * x2);
callback.onNewSample(x, y, z);
i++;
}
}
}
}